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3rd International Winter School and Conference on Network Science : NetSci-X 2017 / / edited by Erez Shmueli, Baruch Barzel, Rami Puzis
| 3rd International Winter School and Conference on Network Science : NetSci-X 2017 / / edited by Erez Shmueli, Baruch Barzel, Rami Puzis |
| Edizione | [1st ed. 2017.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2017 |
| Descrizione fisica | 1 online resource (VI, 130 p. 32 illus., 17 illus. in color.) |
| Disciplina | 004.6 |
| Collana | Springer Proceedings in Complexity |
| Soggetto topico |
Graph theory
Computer simulation Sociology - Methodology System theory Bioinformatics Graph Theory Computer Modelling Sociological Methods Complex Systems Computational and Systems Biology |
| ISBN | 3-319-55471-9 |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Chapter1. Node-Centric Detection of Overlapping Communities in Social Networks -- Chapter2. Community structures evaluation in complex networks: A descriptive approach -- Chapter3. Do Network Models Just Model Networks? On The Applicability of Network Oriented Modeling -- Chapter4. Visibility of nodes in network growth models -- Chapter5. Topology data analysis of critical transitions in financial networks -- Chapter6. Modeling and Analysis of Glass Ceiling and Power Inequality in Bi-populated Societies -- Chapter7. Elites in Social Networks: An Axiomatic Approach -- Chapter8. Ranking scientific papers on the basis of their citations growing trend -- Chapter9. Towards network economics: the problem of the network modus of value -- Chapter10. Open Questions in Multidimensional Multilevel Network Science. . |
| Record Nr. | UNINA-9910254582503321 |
| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2017 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Activation and Detoxification Enzymes : Functions and Implications / / by Chang-Hwei Chen
| Activation and Detoxification Enzymes : Functions and Implications / / by Chang-Hwei Chen |
| Autore | Chen Chang-Hwei |
| Edizione | [2nd ed. 2024.] |
| Pubbl/distr/stampa | Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2024 |
| Descrizione fisica | 1 online resource (257 pages) |
| Disciplina | 574.1925 |
| Soggetto topico |
Human physiology
Enzymology Pharmacology Nutrition Bioinformatics Human Physiology Computational and Systems Biology |
| ISBN | 3-031-55287-3 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Overview -- Foreign Compounds: Foods, Drugs, Chemicals and Life Styles -- Transport and Excretion of Foreign Compounds -- Metabolic Conversion of Foreign Compounds -- Phase I Activation Enzymes -- Phase II Detoxification Enzymes -- Catalytic Reactions of Activation Enzymes -- Catalytic Reactions of Detoxification Enzymes -- Reactive Intermediates and their Interactions -- Metabolite - Associated Cell Toxicities -- Oxidative Stress and Electrophilic Stress -- Metabolic Enzymes: Polymorphism and Species Differences -- Defense Against Oxidative Stress: Nrf2-ARE Pathway -- Inducibility of Metabolic Enzymes -- Inducers of Metabolic Enzymes -- Diversified Classes of Enzyme Modulators -- Metabolite - Mediated Disease Conditions -- Metabolic Enzyme Induction for Health Benefits -- Diet Effects on Metabolic Enzymes. |
| Record Nr. | UNINA-9910847585003321 |
Chen Chang-Hwei
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| Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2024 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Adaptive and Natural Computing Algorithms [[electronic resource] ] : 11th International Conference, ICANNGA 2013, Lausanne, Switzerland, April 4-6, 2013, Proceedings / / edited by Marco Tomassini, Alberto Antonioni, Fabio Daolio, Pierre Buesser
| Adaptive and Natural Computing Algorithms [[electronic resource] ] : 11th International Conference, ICANNGA 2013, Lausanne, Switzerland, April 4-6, 2013, Proceedings / / edited by Marco Tomassini, Alberto Antonioni, Fabio Daolio, Pierre Buesser |
| Edizione | [1st ed. 2013.] |
| Pubbl/distr/stampa | Berlin, Heidelberg : , : Springer Berlin Heidelberg : , : Imprint : Springer, , 2013 |
| Descrizione fisica | 1 online resource (XIV, 506 p. 154 illus.) |
| Disciplina | 005.1 |
| Collana | Theoretical Computer Science and General Issues |
| Soggetto topico |
Computer science
Algorithms Pattern recognition systems Bioinformatics Artificial intelligence Theory of Computation Automated Pattern Recognition Computational and Systems Biology Artificial Intelligence |
| ISBN | 3-642-37213-9 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | On Appropriate Refractoriness and Weight Increment in Incremental Learning.- Vector Generation and Operations in Neural Networks Computations.- Synaptic Scaling Balances Learning in a Spiking Model of Neocortex.- Can Two Hidden Layers Make a Difference.- Time Series Visualization Using Asymmetric Self-Organizing Map.- Intelligence Approaches Based Direct Torque Control of Induction Motor.- Classifier Ensembles Integration with Self-configuring Genetic Programming Algorithm.- A Multi-objective Proposal Based on Firefly Behaviour for Green Scheduling in Grid Systems.- A Framework for Derivative Free Algorithm Hybridization.- PSO-Tagger: A New Biologically Inspired Approach to the Part-of-Speech Tagging Problem.- Training Support Vector Machines with an Heterogeneous Particle Swarm Optimizer.- Fitness Landscape-Based Characterisation of Nature-Inspired Algorithms.- Evolutionary Generation of Small Oscillating Genetic Networks.- Using Scout Particles to Improve a Predator-Prey Optimizer.- QR-DCA: A New Rough Data Pre-processing Approach for the Dendritic Cell Algorithm.- Convergence Rates of Evolutionary Algorithms for Quadratic Convex Functions with Rank-Deficient Hessian.- The Scale-Up Performance of Genetic Algorithms Applied to Group Decision Making Problems.- Using Genetic Programming to Estimate Performance of Computational Intelligence Models.- Multi-caste Ant Colony Algorithm for the Dynamic Traveling Salesperson Problem.- Generalized Information-Theoretic Measures for Feature Selection.- PCA Based Oblique Decision Rules Generating.- Cardinality Problem in Portfolio Selection.- Full and Semi-supervised k-Means Clustering Optimised by Class Membership Hesitation.- Defining Semantic Meta-hashtags for Twitter Classification.- Reinforcement Learning and Genetic Regulatory Network Reconstruction.- Nonlinear Predictive Control Based on Least Squares Support Vector Machines Hammerstein Models.- Particle Swarm Optimization with Transition Probability for Timetabling Problems.- A Consensus Approach for Combining Multiple Classifiers in Cost-Sensitive Bankruptcy Prediction.- On the Regularization Parameter Selection for Sparse Code Learning in Electrical Source Separation.- Region Based Fuzzy Background Subtraction Using Choquet Integral.- A Robust Fuzzy Adaptive Control Algorithm for a Class of Nonlinear Systems.- Disturbance Measurement Utilization in the Efficient MPC Algorithm with Fuzzy Approximations of Nonlinear Models.- Fast Submanifold Learning with Unsupervised Nearest Neighbors.- Using Carrillo-Lipman Approach to Speed up Simultaneous Alignment and Folding of RNA Sequences.- Large Scale Metabolic Characterization Using Flux Balance Analysis and Data Mining.- Automatic Procedures to Assist in Manual Review of Marine Species Distribution Maps.- Mining the Viability Profiles of Different Breast Cancer: A Soft Computing Perspective.- Image Representation and Processing Using Ternary Quantum Computing.- Firefly-Inspired Synchronization of Sensor Networks with Variable Period Lengths.- Phase Transitions in Fermionic Networks.- New Selection Schemes in a Memetic Algorithm for the Vehicle Routing Problem with Time Windows.- Classification Based on the Self-Organization of Child Patients with Developmental Dysphasia.- Similarity Analysis Based on Bose-Einstein Divergences for Financial Time Series.- Exploratory Text Analysis: Data-Driven versus Human Semantic Similarity Judgments.- Linear Support Vector Machines for Error Correction in Optical Data Transmission -- Windows of Driver Gaze Data: How Early and How Much for Robust Predictions of Driver Intent.- Particle Swarm Optimization for Auto-localization of Nodes in Wireless Sensor Networks.- Effective Rule-Based Multi-label Classification with Learning Classifier Systems.- Evolutionary Strategies Algorithm Based Approaches for the Linear Dynamic System Identification.- A Genetic Algorithm Approach for Minimizing the Number of Columnar Runs in a Column Store Table.- Shadow Detection in Complex Images Using Neural Networks: Application to Wine Grape Seed Segmentation -- Vector Generation and Operations in Neural Networks Computations.- Synaptic Scaling Balances Learning in a Spiking Model of Neocortex.- Can Two Hidden Layers Make a Difference.- Time Series Visualization Using Asymmetric Self-Organizing Map.- Intelligence Approaches Based Direct Torque Control of Induction Motor.- Classifier Ensembles Integration with Self-configuring Genetic Programming Algorithm.- A Multi-objective Proposal Based on Firefly Behaviour for Green Scheduling in Grid Systems.- A Framework for Derivative Free Algorithm Hybridization.- PSO-Tagger: A New Biologically Inspired Approach to the Part-of-Speech Tagging Problem.- Training Support Vector Machines with an Heterogeneous Particle Swarm Optimizer.- Fitness Landscape-Based Characterisation of Nature-Inspired Algorithms.- Evolutionary Generation of Small Oscillating Genetic Networks.- Using Scout Particles to Improve a Predator-Prey Optimizer.- QR-DCA: A New Rough Data Pre-processing Approach for the Dendritic Cell Algorithm.- Convergence Rates of Evolutionary Algorithms for Quadratic Convex Functions with Rank-Deficient Hessian.- The Scale-Up Performance of Genetic Algorithms Applied to Group Decision Making Problems.- Using Genetic Programming to Estimate Performance of Computational Intelligence Models.- Multi-caste Ant Colony Algorithm for the Dynamic Traveling Salesperson Problem.- Generalized Information-Theoretic Measures for Feature Selection.- PCA Based Oblique Decision Rules Generating.- Cardinality Problem in Portfolio Selection.- Full and Semi-supervised k-Means Clustering Optimised by Class Membership Hesitation.- Defining Semantic Meta-hashtags for Twitter Classification.- Reinforcement Learning and Genetic Regulatory Network Reconstruction.- Nonlinear Predictive Control Based on Least Squares Support Vector Machines Hammerstein Models.- Particle Swarm Optimization with Transition Probability for Timetabling Problems.- A Consensus Approach for Combining Multiple Classifiers in Cost-Sensitive Bankruptcy Prediction.- On the Regularization Parameter Selection for Sparse Code Learning in Electrical Source Separation.- Region Based Fuzzy Background Subtraction Using Choquet Integral.- A Robust Fuzzy Adaptive Control Algorithm for a Class of Nonlinear Systems.- Disturbance Measurement Utilization in the Efficient MPC Algorithm with Fuzzy Approximations of Nonlinear Models.- Fast Submanifold Learning with Unsupervised Nearest Neighbors.- Using Carrillo-Lipman Approach to Speed up Simultaneous Alignment and Folding of RNA Sequences.- Large Scale Metabolic Characterization Using Flux Balance Analysis and Data Mining.- Automatic Procedures to Assist in Manual Review of Marine Species Distribution Maps.- Mining the Viability Profiles of Different Breast Cancer: A Soft Computing Perspective.- Image Representation and Processing Using Ternary Quantum Computing.- Firefly-Inspired Synchronization of Sensor Networks with Variable Period Lengths.- Phase Transitions in Fermionic Networks.- New Selection Schemes in a Memetic Algorithm for the Vehicle Routing Problem with Time Windows.- Classification Based on the Self-Organization of Child Patients with Developmental Dysphasia.- Similarity Analysis Based on Bose-Einstein Divergences for Financial Time Series.- Exploratory Text Analysis: Data-Driven versus Human Semantic Similarity Judgments.- Linear Support Vector Machines for Error Correction in Optical Data Transmission -- Windows of Driver Gaze Data: How Early and How Much for Robust Predictions of Driver Intent.- Particle Swarm Optimization for Auto-localization of Nodes in Wireless Sensor Networks.- Effective Rule-Based Multi-label Classification with Learning Classifier Systems.- Evolutionary Strategies Algorithm Based Approaches for the Linear Dynamic System Identification.- A Genetic Algorithm Approach for Minimizing the Number of Columnar Runs in a Column Store Table.- Shadow Detection in Complex Images Using Neural Networks: Application to Wine Grape Seed Segmentation. . |
| Record Nr. | UNISA-996465580303316 |
| Berlin, Heidelberg : , : Springer Berlin Heidelberg : , : Imprint : Springer, , 2013 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
| ||
Adaptive and Natural Computing Algorithms : 11th International Conference, ICANNGA 2013, Lausanne, Switzerland, April 4-6, 2013, Proceedings / / edited by Marco Tomassini, Alberto Antonioni, Fabio Daolio, Pierre Buesser
| Adaptive and Natural Computing Algorithms : 11th International Conference, ICANNGA 2013, Lausanne, Switzerland, April 4-6, 2013, Proceedings / / edited by Marco Tomassini, Alberto Antonioni, Fabio Daolio, Pierre Buesser |
| Edizione | [1st ed. 2013.] |
| Pubbl/distr/stampa | Berlin, Heidelberg : , : Springer Berlin Heidelberg : , : Imprint : Springer, , 2013 |
| Descrizione fisica | 1 online resource (XIV, 506 p. 154 illus.) |
| Disciplina | 005.1 |
| Collana | Theoretical Computer Science and General Issues |
| Soggetto topico |
Computer science
Algorithms Pattern recognition systems Bioinformatics Artificial intelligence Theory of Computation Automated Pattern Recognition Computational and Systems Biology Artificial Intelligence |
| ISBN | 3-642-37213-9 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | On Appropriate Refractoriness and Weight Increment in Incremental Learning.- Vector Generation and Operations in Neural Networks Computations.- Synaptic Scaling Balances Learning in a Spiking Model of Neocortex.- Can Two Hidden Layers Make a Difference.- Time Series Visualization Using Asymmetric Self-Organizing Map.- Intelligence Approaches Based Direct Torque Control of Induction Motor.- Classifier Ensembles Integration with Self-configuring Genetic Programming Algorithm.- A Multi-objective Proposal Based on Firefly Behaviour for Green Scheduling in Grid Systems.- A Framework for Derivative Free Algorithm Hybridization.- PSO-Tagger: A New Biologically Inspired Approach to the Part-of-Speech Tagging Problem.- Training Support Vector Machines with an Heterogeneous Particle Swarm Optimizer.- Fitness Landscape-Based Characterisation of Nature-Inspired Algorithms.- Evolutionary Generation of Small Oscillating Genetic Networks.- Using Scout Particles to Improve a Predator-Prey Optimizer.- QR-DCA: A New Rough Data Pre-processing Approach for the Dendritic Cell Algorithm.- Convergence Rates of Evolutionary Algorithms for Quadratic Convex Functions with Rank-Deficient Hessian.- The Scale-Up Performance of Genetic Algorithms Applied to Group Decision Making Problems.- Using Genetic Programming to Estimate Performance of Computational Intelligence Models.- Multi-caste Ant Colony Algorithm for the Dynamic Traveling Salesperson Problem.- Generalized Information-Theoretic Measures for Feature Selection.- PCA Based Oblique Decision Rules Generating.- Cardinality Problem in Portfolio Selection.- Full and Semi-supervised k-Means Clustering Optimised by Class Membership Hesitation.- Defining Semantic Meta-hashtags for Twitter Classification.- Reinforcement Learning and Genetic Regulatory Network Reconstruction.- Nonlinear Predictive Control Based on Least Squares Support Vector Machines Hammerstein Models.- Particle Swarm Optimization with Transition Probability for Timetabling Problems.- A Consensus Approach for Combining Multiple Classifiers in Cost-Sensitive Bankruptcy Prediction.- On the Regularization Parameter Selection for Sparse Code Learning in Electrical Source Separation.- Region Based Fuzzy Background Subtraction Using Choquet Integral.- A Robust Fuzzy Adaptive Control Algorithm for a Class of Nonlinear Systems.- Disturbance Measurement Utilization in the Efficient MPC Algorithm with Fuzzy Approximations of Nonlinear Models.- Fast Submanifold Learning with Unsupervised Nearest Neighbors.- Using Carrillo-Lipman Approach to Speed up Simultaneous Alignment and Folding of RNA Sequences.- Large Scale Metabolic Characterization Using Flux Balance Analysis and Data Mining.- Automatic Procedures to Assist in Manual Review of Marine Species Distribution Maps.- Mining the Viability Profiles of Different Breast Cancer: A Soft Computing Perspective.- Image Representation and Processing Using Ternary Quantum Computing.- Firefly-Inspired Synchronization of Sensor Networks with Variable Period Lengths.- Phase Transitions in Fermionic Networks.- New Selection Schemes in a Memetic Algorithm for the Vehicle Routing Problem with Time Windows.- Classification Based on the Self-Organization of Child Patients with Developmental Dysphasia.- Similarity Analysis Based on Bose-Einstein Divergences for Financial Time Series.- Exploratory Text Analysis: Data-Driven versus Human Semantic Similarity Judgments.- Linear Support Vector Machines for Error Correction in Optical Data Transmission -- Windows of Driver Gaze Data: How Early and How Much for Robust Predictions of Driver Intent.- Particle Swarm Optimization for Auto-localization of Nodes in Wireless Sensor Networks.- Effective Rule-Based Multi-label Classification with Learning Classifier Systems.- Evolutionary Strategies Algorithm Based Approaches for the Linear Dynamic System Identification.- A Genetic Algorithm Approach for Minimizing the Number of Columnar Runs in a Column Store Table.- Shadow Detection in Complex Images Using Neural Networks: Application to Wine Grape Seed Segmentation -- Vector Generation and Operations in Neural Networks Computations.- Synaptic Scaling Balances Learning in a Spiking Model of Neocortex.- Can Two Hidden Layers Make a Difference.- Time Series Visualization Using Asymmetric Self-Organizing Map.- Intelligence Approaches Based Direct Torque Control of Induction Motor.- Classifier Ensembles Integration with Self-configuring Genetic Programming Algorithm.- A Multi-objective Proposal Based on Firefly Behaviour for Green Scheduling in Grid Systems.- A Framework for Derivative Free Algorithm Hybridization.- PSO-Tagger: A New Biologically Inspired Approach to the Part-of-Speech Tagging Problem.- Training Support Vector Machines with an Heterogeneous Particle Swarm Optimizer.- Fitness Landscape-Based Characterisation of Nature-Inspired Algorithms.- Evolutionary Generation of Small Oscillating Genetic Networks.- Using Scout Particles to Improve a Predator-Prey Optimizer.- QR-DCA: A New Rough Data Pre-processing Approach for the Dendritic Cell Algorithm.- Convergence Rates of Evolutionary Algorithms for Quadratic Convex Functions with Rank-Deficient Hessian.- The Scale-Up Performance of Genetic Algorithms Applied to Group Decision Making Problems.- Using Genetic Programming to Estimate Performance of Computational Intelligence Models.- Multi-caste Ant Colony Algorithm for the Dynamic Traveling Salesperson Problem.- Generalized Information-Theoretic Measures for Feature Selection.- PCA Based Oblique Decision Rules Generating.- Cardinality Problem in Portfolio Selection.- Full and Semi-supervised k-Means Clustering Optimised by Class Membership Hesitation.- Defining Semantic Meta-hashtags for Twitter Classification.- Reinforcement Learning and Genetic Regulatory Network Reconstruction.- Nonlinear Predictive Control Based on Least Squares Support Vector Machines Hammerstein Models.- Particle Swarm Optimization with Transition Probability for Timetabling Problems.- A Consensus Approach for Combining Multiple Classifiers in Cost-Sensitive Bankruptcy Prediction.- On the Regularization Parameter Selection for Sparse Code Learning in Electrical Source Separation.- Region Based Fuzzy Background Subtraction Using Choquet Integral.- A Robust Fuzzy Adaptive Control Algorithm for a Class of Nonlinear Systems.- Disturbance Measurement Utilization in the Efficient MPC Algorithm with Fuzzy Approximations of Nonlinear Models.- Fast Submanifold Learning with Unsupervised Nearest Neighbors.- Using Carrillo-Lipman Approach to Speed up Simultaneous Alignment and Folding of RNA Sequences.- Large Scale Metabolic Characterization Using Flux Balance Analysis and Data Mining.- Automatic Procedures to Assist in Manual Review of Marine Species Distribution Maps.- Mining the Viability Profiles of Different Breast Cancer: A Soft Computing Perspective.- Image Representation and Processing Using Ternary Quantum Computing.- Firefly-Inspired Synchronization of Sensor Networks with Variable Period Lengths.- Phase Transitions in Fermionic Networks.- New Selection Schemes in a Memetic Algorithm for the Vehicle Routing Problem with Time Windows.- Classification Based on the Self-Organization of Child Patients with Developmental Dysphasia.- Similarity Analysis Based on Bose-Einstein Divergences for Financial Time Series.- Exploratory Text Analysis: Data-Driven versus Human Semantic Similarity Judgments.- Linear Support Vector Machines for Error Correction in Optical Data Transmission -- Windows of Driver Gaze Data: How Early and How Much for Robust Predictions of Driver Intent.- Particle Swarm Optimization for Auto-localization of Nodes in Wireless Sensor Networks.- Effective Rule-Based Multi-label Classification with Learning Classifier Systems.- Evolutionary Strategies Algorithm Based Approaches for the Linear Dynamic System Identification.- A Genetic Algorithm Approach for Minimizing the Number of Columnar Runs in a Column Store Table.- Shadow Detection in Complex Images Using Neural Networks: Application to Wine Grape Seed Segmentation. . |
| Record Nr. | UNINA-9910483197203321 |
| Berlin, Heidelberg : , : Springer Berlin Heidelberg : , : Imprint : Springer, , 2013 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Advanced Intelligent Computing in Bioinformatics : 20th International Conference, ICIC 2024, Tianjin, China, August 5–8, 2024, Proceedings, Part I / / edited by De-Shuang Huang, Qinhu Zhang, Jiayang Guo
| Advanced Intelligent Computing in Bioinformatics : 20th International Conference, ICIC 2024, Tianjin, China, August 5–8, 2024, Proceedings, Part I / / edited by De-Shuang Huang, Qinhu Zhang, Jiayang Guo |
| Edizione | [1st ed. 2024.] |
| Pubbl/distr/stampa | Singapore : , : Springer Nature Singapore : , : Imprint : Springer, , 2024 |
| Descrizione fisica | 1 online resource (490 pages) |
| Disciplina | 572.80285 |
| Collana | Lecture Notes in Bioinformatics |
| Soggetto topico |
Computational intelligence
Artificial intelligence Bioinformatics Computational Intelligence Artificial Intelligence Computational and Systems Biology Bioinformàtica Intel·ligència computacional Intel·ligència artificial |
| Soggetto genere / forma |
Congressos
Llibres electrònics |
| ISBN | 981-9756-89-8 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Intro -- Preface -- Organization -- Contents - Part I -- Contents - Part II -- Biomedical Data Modeling and Mining -- Alzheimer's Disease Diagnosis via Specific-Shared Representation Learning in Multimodal Neuroimaging -- 1 Introduction -- 2 Method -- 2.1 Overview -- 2.2 Shallow Feature Learning -- 2.3 Modality Specific Representation Learning -- 2.4 Modality Shared Representation Learning -- 2.5 Modality Specific-Shared Representation Learning -- 3 Experiments -- 3.1 Materials and Image Pre-processing -- 3.2 Comparison Methods -- 3.3 Experimental Setup -- 3.4 Evaluation of Automated Diseases Diagnosis -- 3.5 Ablation Study -- 4 Conclusion -- References -- An Activity Graph-Based Deep Convolutional Neural Network Framework in Symptom Severity Diagnosis Towards Parkinson's Disease Using Inertial Sensors -- 1 Introduction -- 2 Subjects and Data Collection -- 2.1 Participants -- 2.2 Data Collection -- 3 Methodology -- 3.1 Activity Graph Generation -- 3.2 Data Augmentation -- 3.3 Convolutional Neural Network -- 4 Results -- 5 Discussion and Conclusion -- References -- An Optimization Method for Drug Design Based on Molecular Features -- 1 Introduction -- 2 Methods -- 2.1 Pocket of Targeted Protein -- 2.2 Feature Extraction of Targeted Protein -- 2.3 Feature Representation of Drug Molecule -- 2.4 Model -- 3 Experimental Results -- 3.1 Datasets -- 3.2 Comparison of Experiments -- 4 Conclusion -- References -- Application of Machine Learning and Large Language Model Module for Analyzing Gut Microbiota Data -- 1 Introduction -- 2 Methodology -- 2.1 Overview -- 2.2 Machine Learning Algorithms -- 2.3 Chat2GM - a LLM Module Based on Langchain Framework -- 3 Applications and Analysis -- 3.1 Data -- 3.2 Species Diversity Analysis with Statistical Methods -- 3.3 Identification of Obesity-Related Biomarkers via Machine Learning.
3.4 Gut Microbiota Data Analysis with Chat2GM Module -- 4 Conclusions -- References -- CVAE-Based Hybrid Sampling Data Augmentation Method and Interpretation for Imbalanced Classification of Gout Disease -- 1 Introduction -- 2 Materials and Methods -- 2.1 CVAE-Based Hybrid Sampling -- 2.2 Detection Model -- 2.3 Interpretation -- 3 Experiment and Result -- 3.1 Datasets -- 3.2 Classification Results -- 3.3 Comparison of Balancing Strategies -- 3.4 Model Interpretation -- 4 Conclusion -- References -- DepthParkNet: A 3D Convolutional Neural Network with Depth-Aware Coordinate Attention for PET-Based Parkinson's Disease Diagnosis -- 1 Introduction -- 2 Method -- 2.1 Depth-Aware Coordinate Attention -- 2.2 PDaug -- 2.3 Class-Balanced Loss -- 3 Experiments -- 3.1 Datasets and Preprocessing -- 3.2 Implementation Details -- 3.3 Comparison -- 3.4 Ablation Study -- 4 Conclusion -- References -- Gene Selection and Classification Method Based on SNR and Multi-loops BPSO -- 1 Introduction -- 2 Method -- 2.1 The Multi-loops BPSO -- 3 Experiments and Results -- 3.1 Experiment Preparation -- 3.2 Experimental Design Principles -- 3.3 Preprocessing by SNR -- 3.4 The Comparison of One-Loop and Multi-loops on BPSO -- 3.5 Comparative Experiment and Analysis -- 4 Conclusion -- References -- Graph Convolutional Networks Based Multi-modal Data Integration for Breast Cancer Survival Prediction -- 1 Introduction -- 2 Method -- 2.1 Feature Selection and Fusion -- 2.2 Patient-Patient Graph Construction -- 2.3 Multi-modal Graph Convolutional Networks Module -- 2.4 Training Details -- 3 Experiments -- 3.1 Datasets and Evaluation Metrics -- 3.2 Comparisons with State-of-The-Art -- 3.3 Ablation Studies -- 3.4 Validation -- 4 Conclusion and Future Work -- References -- IDHPre: Intradialytic Hypotension Prediction Model Based on Fully Observed Features -- 1 Introduction. 2 Related Work -- 2.1 Imputation of Missing Values -- 2.2 Feature Selection -- 3 IDHPre -- 3.1 Imputation of Missing Values -- 3.2 Feature Selection -- 4 Experiment and Evaluation -- 4.1 Implementation Details -- 4.2 Qualitative and Quantitative Comparison -- 4.3 Ablation Study -- 5 Conclusion -- References -- Machine Learning Models for Improved Cell Screening -- 1 Introduction -- 2 Related Work -- 2.1 Mainstream Cell Line Screening Methods -- 2.2 Model Stacking -- 3 Dataset -- 4 Proposed Methods -- 4.1 Stacked Machine Learning Method (SMLM) -- 4.2 Simple Linear Method (SLM) -- 4.3 Model Characteristics and Applicability Analysis -- 5 Experimental Results -- 5.1 Experimental Setup -- 5.2 Experimental Analysis -- 6 Conclusion and Pen Question -- References -- Prediction of Bladder Cancer Prognosis by Deep Cox Proportional Hazards Model Based on Adversarial Autoencoder -- 1 Introduction -- 2 Methods -- 2.1 The Framework of the Study -- 2.2 Adversarial Autoencoders -- 2.3 The Architecture of AAE-Cox -- 3 Results -- 3.1 Datasets -- 3.2 Experiments -- 3.3 Evaluations of Cancer Outcomes Prediction -- 3.4 Method Comparison -- 3.5 Independent Test -- 3.6 Identification of Cancer-Related Prognostic Markers and Pathways -- 4 Conclusion and Discussion -- References -- SGEGCAE: A Sparse Gating Enhanced Graph Convolutional Autoencoder for Multi-omics Data Integration and Classification -- 1 Introduction -- 2 Methods -- 2.1 Overview of SGEGCAE -- 2.2 AE for Attribute Information Representation -- 2.3 EGCAE for Feature Representations -- 2.4 Sparse Gating Strategy for Enhanced Feature Representations -- 2.5 TCP for Omics Informativeness Estimation -- 2.6 TFN for Multi-omics Integration -- 3 Experiments and Results -- 3.1 Datasets and Evaluation Metrics -- 3.2 Analysis of Classification Results -- 3.3 Ablation Studies -- 3.4 Analysis of Hyper-parameter. 3.5 Analysis of Different Omics Data Types -- 4 Conclusion -- References -- Short-Term Blood Glucose Prediction Method Based on Signal Decomposition and Bidirectional Networks -- 1 Introduction -- 2 Short-Term Blood Glucose Prediction Method Based on Signal Decomposition and Bidirectional Networks -- 2.1 Overall Approach -- 2.2 Variation Mode Decomposition Algorithm Based on Sparrow Search -- 2.3 Composite Network of Bidirectional Gated Recurrent Unit (BiGRU) and Bidirectional Long Short-Term Memory (BiLSTM) -- 3 Results and Analysis -- 3.1 Experimental Environment and Parameter Settings -- 3.2 Model Performance Evaluation Metrics -- 3.3 Model Performance Evaluation Metrics -- 4 Conclusion -- References -- SLGNNCT: Synthetic Lethality Prediction Based on Knowledge Graph for Different Cancers Types -- 1 Introduction -- 2 Dataset -- 3 Method -- 3.1 Knowledge Graph Level Gene Embedding Generation -- 3.2 Message Aggregation Based on Factors -- 3.3 Calculation of Synthetic Lethal Interaction Probabilities -- 4 Experiment -- 4.1 Baselines -- 4.2 Model Evaluation -- 4.3 Results and Analysis of Ablation Experiments -- 5 Conclusion -- References -- TransPBMIL: Transformer-Based Weakly Supervised Prognostic Prediction in Ovarian Cancer with Pseudo-Bag Strategy -- 1 Introduction -- 2 Materials and Methods -- 2.1 Participants and Dataset Generation -- 2.2 TransPBMIL Framework -- 3 Result -- 3.1 Comparison with Existing Weakly Supervised Works -- 3.2 The Performance Improvement Brought by the Pseudo-Bag Strategy. -- 3.3 Visualization of Detection Results -- 4 Conclusion -- References -- Biomedical Informatics Theory and Methods -- A Heterogeneous Cross Contrastive Learning Method for Drug-Target Interaction Prediction -- 1 Introduction -- 2 Method -- 2.1 Graph Embedding Module -- 2.2 Self-contrast Module -- 2.3 Cross-Contrast Module. 2.4 Pairwise Judgment Module -- 3 Experiments -- 3.1 Datasets -- 3.2 Experimental Settings -- 3.3 Experimental Results. -- 3.4 Parameter Sensitivity Analysis. -- 4 Conclusion -- References -- A Retrieval-Based Molecular Style Transformation Optimization Model -- 1 Introduction -- 2 Methods -- 2.1 Overview -- 2.2 Molecular Retriever -- 2.3 Information Fusion Module and Decoder -- 2.4 Retrieval-Based Molecular Style Transformation Generative Network -- 3 Results -- 3.1 Datasets and Performance Metrics -- 3.2 Results on the QED and PlogP Tasks -- 3.3 Ablation Experiments -- 3.4 Visualized Optimization Results -- 3.5 Parameter Analysis -- 4 Conclusion -- References -- Aggregation Strategy with Gradient Projection for Federated Learning in Diagnosis -- 1 Introduction -- 2 Method -- 2.1 Problem Definition -- 2.2 Federal Projection Matrix -- 2.3 Local Training with GPM -- 3 Experiment -- 3.1 Datasets and Experiment Settings -- 3.2 Implementation Details -- 3.3 Evaluation and Discussion -- 3.4 Ablation Studies -- 4 Conclusion -- References -- Coronary Artery 3D/2D Registration Based on Particle Swarm Optimization of Contextual Morphological Features -- 1 Introduction -- 2 Proposed Method -- 2.1 DSA Vessel Intersection Extraction -- 2.2 CTA Vessel Intersection Extraction -- 2.3 3D-2D Vessel Matching Based on PSO -- 3 Experiments and Results -- 3.1 DSA Vessel Intersection Extraction Results -- 3.2 Results of CTA Vascular Center Line and Intersection -- 3.3 Results of Vascular Matching Between CTA and DSA -- 4 Conclusions -- References -- Enhancing Drug-Drug Interaction Predictions in Biomedical Knowledge Graphs Through Integration of Householder Projections and Capsule Network Techniques -- 1 Introduction -- 2 Preliminaries -- 2.1 Projective Space -- 2.2 Advanced Formulation of Householder Projections -- 3 Model -- 3.1 Relational Householder Projections. 3.2 Möbius Representation Transformation. |
| Record Nr. | UNINA-9910878049003321 |
| Singapore : , : Springer Nature Singapore : , : Imprint : Springer, , 2024 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Advanced Intelligent Computing in Bioinformatics : 20th International Conference, ICIC 2024, Tianjin, China, August 5–8, 2024, Proceedings, Part II / / edited by De-Shuang Huang, Yijie Pan, Qinhu Zhang
| Advanced Intelligent Computing in Bioinformatics : 20th International Conference, ICIC 2024, Tianjin, China, August 5–8, 2024, Proceedings, Part II / / edited by De-Shuang Huang, Yijie Pan, Qinhu Zhang |
| Edizione | [1st ed. 2024.] |
| Pubbl/distr/stampa | Singapore : , : Springer Nature Singapore : , : Imprint : Springer, , 2024 |
| Descrizione fisica | 1 online resource (505 pages) |
| Disciplina | 572.80285 |
| Collana | Lecture Notes in Bioinformatics |
| Soggetto topico |
Computational intelligence
Artificial intelligence Bioinformatics Computational Intelligence Artificial Intelligence Computational and Systems Biology Bioinformàtica Intel·ligència artificial Intel·ligència computacional |
| Soggetto genere / forma |
Congressos
Llibres electrònics |
| ISBN | 981-9756-92-8 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Intro -- Preface -- Organization -- Contents - Part II -- Contents - Part I -- Biomedical Data Modeling and Mining -- AAHLDMA: Predicting Drug-Microbe Associations Based on Bridge Graph Learning -- 1 Introduction -- 2 Materials -- 2.1 Drug Similarity Attribute -- 2.2 Drug Network Topological Attribute -- 2.3 Fused Drug Attribute -- 2.4 Microbe Functional Similarity Attribute -- 2.5 Microbe Sequence Attribute -- 2.6 Fused Microbe Attribute -- 3 Methods -- 3.1 Attention-Based Graph Autoencoder -- 3.2 Construction of Bridge Graph -- 3.3 Classification -- 4 Experiment -- 4.1 Experimental Setup -- 4.2 Model Performance -- 4.3 Performance Comparison with Other Models -- 4.4 Case Study -- 5 Conclusion -- References -- Adaptive Weight Sampling and Graph Transformer Neural Network Framework for Cell Type Annotation of Scrna-seq Data -- 1 Introduction -- 2 Materials -- 2.1 scRNA-seq Datasets -- 2.2 Gene Interaction Networks -- 3 Methods -- 3.1 Adaptive Sampling -- 3.2 Graph Representation Module -- 4 Experimental Results -- 4.1 Model ACC Performance -- 4.2 Model ACC Performance -- 4.3 Sankey Diagram Representation of the Model on the Data Set -- 5 Conclusion -- References -- BiLETCR: An Efficient PMHC-TCR Combined Forecasting Method -- 1 Introduction -- 2 Related Work -- 3 Methodology -- 3.1 BiLETCR Model Structure and Forecasting Process -- 3.2 EMA -- 3.3 Model Training -- 4 Experiments -- 4.1 Data Collection and Processing -- 4.2 Experimental Design -- 4.3 Adding EMA Module Can Improve the Performance of the Model -- 4.4 For the Generalization Test of BiLETCR, the Prediction Effect of BiLETCR is Better Than the Existing Model -- 4.5 BiLETCR is Superior to the Existing Model in Computational Efficiency -- 4.6 BiLETCR is Superior to the Existing Prediction Tools on Ts-Special Test Set -- 5 Conclusion -- References.
CDDTR: Cross-Domain Autoencoders for Predicting Cell Type Specific Drug-Induced Transcriptional Responses -- 1 Introduction -- 2 Materials and Methods -- 2.1 Within-Domain Reconstruction Paths -- 2.2 Cross-Domain Reconstruction Paths -- 2.3 Training and Prediction Procedures -- 2.4 Comparison with Alternative Methods -- 3 Results -- 3.1 Comparison Results with the State-of-the-Art Methods -- 3.2 The Performance of CDDTR on Small Sample Data -- 3.3 Biological Interpretability of CDDTR Model -- 3.4 Further Improvement of Prediction Performance of CDDTR -- 3.5 Case Study -- 4 Conclusion and Discussion -- References -- ChiMamba: Predicting Chromatin Interactions Based on Mamba -- 1 Introduction -- 2 Materials and Methods -- 2.1 Datasets and Processing -- 2.2 Selective State Space Models -- 2.3 ChiMamba Model -- 3 Experiment -- 3.1 Datasets and Experiment Setup -- 3.2 Comparative Studies -- 3.3 Ablation Studies -- 3.4 Training Time -- 4 Discussion -- References -- Cluster Analysis of Scrna-Seq Data Combining Bioinformatics with Graph Attention Autoencoders and Ensemble Clustering -- 1 Introduction -- 2 Materials -- 2.1 Dataset -- 2.2 Processing Gene Expression Matrix -- 2.3 Denoising Using Network Enhancement -- 2.4 Performing Principal Component Analysis -- 3 Methods -- 3.1 Graph Attention Autoencoder -- 3.2 Bipartite Graph Ensemble Clustering Method -- 4 Experimental Results -- 4.1 Model Performance -- 4.2 Comparison of Different Model -- 4.3 Comparison of Different Datasets -- 5 Conclusion -- References -- Compound-Protein Interaction Prediction with Sparse Perturbation-Aware Attention -- 1 Introduction -- 2 Methodology -- 2.1 Prediction Backbone -- 2.2 Perturbation-Aware Attention -- 3 Experiments -- 3.1 Experimental Setup -- 3.2 Implementation Details -- 3.3 Comparative Performance -- 3.4 Impacts of Modules and Parameters -- 3.5 Case Study. 4 Related Work -- 5 Conclusion -- References -- CUK-Band: A CUDA-Based Multiple Genomic Sequence Alignment on GPU -- 1 Introduction -- 2 Related Work -- 3 Methodology -- 3.1 The Strategy of Affine Gap Penalty and K-band -- 3.2 Improved Central Star Strategy Based on Bitmap -- 3.3 The K-band Strategy Based on CUDA -- 4 Performance Evaluation -- 4.1 Datasets and Evaluation Criterion -- 4.2 Configuration -- 4.3 Results -- 5 Conclusion -- References -- DeepMHAttGRU-DTI: Prediction of Drug-Target Interactions Based on Knowledge Graph Random Walk Embeddings and GRU Neural Network -- 1 Introduction -- 2 Materials and Methods -- 2.1 Graph Embedding Algorithm Based on Three Improved Random Walk Algorithms -- 2.2 GRU Binary Classification Neural Network Model -- 2.3 Multi-head Attention -- 3 Experimental Results -- 3.1 Evaluation Criteria -- 3.2 General Dataset -- 3.3 Comparison of Different Random Walk Algorithms Using GRU Model -- 3.4 Comparison Between the GRU Model and the MHAttGRU Model -- 3.5 Comparison with Other Existing Models -- 4 Conclusion -- References -- DiagNCF: Diagnosis Neural Collaborative Filtering for Accurate Medical Recommendation -- 1 Introduction -- 2 Preliminaries -- 2.1 Setup and Notation -- 2.2 Data-Preprocessing -- 3 Diagnose Neural Collaborative Filtering (DiagNCF) -- 3.1 General Framework -- 3.2 Generalized Matrix Factorization (GMF) -- 3.3 Multi-Layer Perception (MLP) -- 3.4 DiagNCF -- 4 Experiments -- 4.1 Performance Evaluation -- 4.2 Training Procedure -- 5 Conclusions -- References -- Drug Molecule Generation Method Based on Fusion of Protein Sequence Features -- 1 Introduction -- 2 Methods -- 2.1 Datasets -- 2.2 Targeted Drug Generation Process -- 3 Experimental Results -- 3.1 Evaluation of Model Performance -- 3.2 Molecular Docking Results -- 4 Conclusion -- References. Drug Target Affinity Prediction Based on Graph Structural Enhancement and Multi-scale Topological Feature Fusion -- 1 Introduction -- 2 Methods -- 2.1 Model Architecture -- 2.2 Drug Feature Extraction Module -- 2.3 Protein Feature Extraction Module -- 2.4 Multi-scale Topological Feature Fusion Module -- 3 Results and Discussion -- 3.1 Datasets -- 3.2 Evaluation Metrics -- 3.3 Parameters Setting -- 3.4 Performance Comparison with Baseline Model -- 4 Ablation Experiment -- 5 Conclusion -- References -- Drug-Target Interaction Prediction Based on Multi-path Graph Convolution and Graph-Level Attention Mechanism -- 1 Introduction -- 2 Methods -- 2.1 Method Overview -- 2.2 Feature Extraction -- 2.3 Multi-feature Graph Convolution Module -- 2.4 Loss Function -- 3 Results -- 3.1 Dataset -- 3.2 Experiment Settings -- 3.3 Comparisons with Other Baseline Methods -- 3.4 Ablation Experiments -- 3.5 Model Generalization Test -- 4 Conclusion -- References -- Fully Convolutional Neural Network for Predicting Cancer-Specific CircRNA-MiRNA Interaction Sites -- 1 Introduction -- 2 Materials and Methods -- 2.1 Data -- 2.2 Modelling -- 3 Results -- 4 Discussion and Conclusion -- References -- GSDPI: An Integrated Feature Extraction Framework for Predicting Novel Drug-Protein Interaction -- 1 Introduction -- 2 Materials and Methods -- 2.1 Datasets -- 2.2 Low-Dimensional Feature Vectors and Feature Similarity Matrices -- 2.3 Determining the Dimensionality of Feature Matrix -- 2.4 Calculation of the Feature Similarity Matrices -- 2.5 DPI Prediction Model Based on GSDPI -- 3 Experimental Evaluation -- 3.1 Evaluation Metrics -- 3.2 Method Comparison and Parameter Settings -- 3.3 Experimental Comparison -- 3.4 Ablation Experiments -- 3.5 Integrate the Gene Ontology (GO) Annotation for All Drug Target-Coding Genes -- 3.6 Case Study -- 4 Conclusion -- References. Heterogeneous Genome Compression on Mobile Devices -- 1 Introduction -- 2 Related Works -- 2.1 Genome Data Compression -- 2.2 Hardware Accelerated Bioinformatics -- 3 Background -- 3.1 Heterogeneity of MPSoC -- 3.2 Dynamic Voltage-Frequency Scaling -- 4 Methods -- 4.1 Distribute Tasks Transparently -- 4.2 Pipeline Organization -- 5 Results and Discussions -- 5.1 Test Data -- 5.2 Performance and Energy Efficiency Improvements of Heterogeneous Gzip -- 5.3 Exploration for the Reason of Extra Energy Consumption and Discussion -- 6 Conclusion -- References -- HyperCPI: A Novel Method Based on Hypergraph for Compound Protein Interaction Prediction with Good Generalization Ability -- 1 Introduction -- 2 Materials and Methods -- 2.1 Datasets -- 2.2 Hypergraphs -- 2.3 Model Architecture of HyperCPI -- 3 Results and Discussion -- 3.1 Performance on OOD Experiments -- 3.2 Ablation Study -- 4 Conclusion -- References -- iEMNN: An Iterative Integration Method for Single-Cell Transcriptomic Data Based on Network Similarity Enhancement and Mutual Nearest Neighbors -- 1 Introduction -- 2 Materials and Methods -- 2.1 Overview of iEMNN -- 2.2 Network Similarity Enhancement -- 2.3 Methods for Comparison -- 2.4 Performance Metrics -- 3 Results -- 3.1 iEMNN Enhances the Similarity of Similar Cells While Separating Distinct Cells -- 3.2 Scenario 1: iEMNN in the Scenario of Identical Cell Types -- 3.3 Scenario 2: iEMNN in the Scenario of Non-identical Cell Types -- 3.4 Scenario 3: iEMNN in the Scenario of Multiple Batches -- 3.5 Scenario 4: iEMNN in the Scenario of Cross-Species -- 4 Discussion -- References -- IGDACA: Imaging Genomics of Deep Autoencoder Cascade Attention Fusion Networks for Cervical Cancer Prognosis Prediction -- 1 Introduction -- 2 Method -- 2.1 Model Design -- 2.2 Image Feature Extraction -- 2.3 Gene Feature Extraction -- 2.4 Attention Fusion Module. 3 Experiments and Analyses. |
| Record Nr. | UNINA-9910878052503321 |
| Singapore : , : Springer Nature Singapore : , : Imprint : Springer, , 2024 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Advances in Artificial Intelligence, Computation, and Data Science : For Medicine and Life Science / / edited by Tuan D. Pham, Hong Yan, Muhammad W. Ashraf, Folke Sjöberg
| Advances in Artificial Intelligence, Computation, and Data Science : For Medicine and Life Science / / edited by Tuan D. Pham, Hong Yan, Muhammad W. Ashraf, Folke Sjöberg |
| Edizione | [1st ed. 2021.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2021 |
| Descrizione fisica | 1 online resource (373 pages) |
| Disciplina | 610.285 |
| Collana | Computational Biology |
| Soggetto topico |
Bioinformatics
Artificial intelligence Artificial intelligence - Data processing Computer science Biomathematics Image processing - Digital techniques Computer vision Computational and Systems Biology Artificial Intelligence Data Science Theory of Computation Mathematical and Computational Biology Computer Imaging, Vision, Pattern Recognition and Graphics Intel·ligència artificial en medicina Investigació mèdica Ciències de la vida Processament de dades |
| Soggetto genere / forma | Llibres electrònics |
| ISBN | 3-030-69951-X |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Part I: Review of Recent Developments in AI, Computational Models for Complex Data Analysis, and Data Science -- 1. Recent Developments in AI -- 2. Recent Developments in Computational Models for Data Analysis -- 3. Recent Developments in Data Science -- Part II: Applications in Medicine and Physiology -- 4. Cancer -- 5. Neuroscience -- 6. Cardiology -- 7. Critical Care -- 8. Health Care -- 9. Digital Pathology -- Part III: Applications in Life Science -- 10. Systems Biology -- 11. Cell Biology -- 12. Biochemistry -- 13. Chemo-metrics -- 14. Food Technology. |
| Record Nr. | UNINA-9910492152303321 |
| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2021 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Advances in Artificial Intelligence, Computation, and Data Science : For Medicine and Life Science / / edited by Tuan D. Pham, Hong Yan, Muhammad W. Ashraf, Folke Sjöberg
| Advances in Artificial Intelligence, Computation, and Data Science : For Medicine and Life Science / / edited by Tuan D. Pham, Hong Yan, Muhammad W. Ashraf, Folke Sjöberg |
| Edizione | [1st ed. 2021.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2021 |
| Descrizione fisica | 1 online resource (373 pages) |
| Disciplina | 610.285 |
| Collana | Computational Biology |
| Soggetto topico |
Bioinformatics
Artificial intelligence Artificial intelligence - Data processing Computer science Biomathematics Image processing - Digital techniques Computer vision Computational and Systems Biology Artificial Intelligence Data Science Theory of Computation Mathematical and Computational Biology Computer Imaging, Vision, Pattern Recognition and Graphics Intel·ligència artificial en medicina Investigació mèdica Ciències de la vida Processament de dades |
| Soggetto genere / forma | Llibres electrònics |
| ISBN | 3-030-69951-X |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Part I: Review of Recent Developments in AI, Computational Models for Complex Data Analysis, and Data Science -- 1. Recent Developments in AI -- 2. Recent Developments in Computational Models for Data Analysis -- 3. Recent Developments in Data Science -- Part II: Applications in Medicine and Physiology -- 4. Cancer -- 5. Neuroscience -- 6. Cardiology -- 7. Critical Care -- 8. Health Care -- 9. Digital Pathology -- Part III: Applications in Life Science -- 10. Systems Biology -- 11. Cell Biology -- 12. Biochemistry -- 13. Chemo-metrics -- 14. Food Technology. |
| Record Nr. | UNISA-996464404503316 |
| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2021 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
| ||
Advances in Artificial Life : 5th European Conference, ECAL'99, Lausanne, Switzerland, September 13-17, 1999 Proceedings / / edited by Dario Floreano, Jean-Daniel Nicoud, Francesco Mondada
| Advances in Artificial Life : 5th European Conference, ECAL'99, Lausanne, Switzerland, September 13-17, 1999 Proceedings / / edited by Dario Floreano, Jean-Daniel Nicoud, Francesco Mondada |
| Edizione | [1st ed. 1999.] |
| Pubbl/distr/stampa | Berlin, Heidelberg : , : Springer Berlin Heidelberg : , : Imprint : Springer, , 1999 |
| Descrizione fisica | 1 online resource (XVIII, 742 p.) |
| Disciplina | 570.113 |
| Collana | Lecture Notes in Artificial Intelligence |
| Soggetto topico |
Artificial intelligence
Automatic control Robotics Automation Bioinformatics Computer science Artificial Intelligence Control, Robotics, Automation Computational and Systems Biology Theory of Computation |
| ISBN | 3-540-48304-7 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Keynote Lectures -- Epistemology -- Evolutionary Dynamics -- Evolutionary Cybernetics -- Bio-inspired Robotics and Autonomous Agents -- Self-Replication, Self-Maintenance, and Gene Expression -- Societies and Collective Behaviour -- Communication and Language. |
| Record Nr. | UNINA-9910144148603321 |
| Berlin, Heidelberg : , : Springer Berlin Heidelberg : , : Imprint : Springer, , 1999 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Advances in Bioinformatics, Multimedia, and Electronics Circuits and Signals : Proceedings of GUCON 2019 / / edited by Lakhmi C. Jain, Maria Virvou, Vincenzo Piuri, Valentina E. Balas
| Advances in Bioinformatics, Multimedia, and Electronics Circuits and Signals : Proceedings of GUCON 2019 / / edited by Lakhmi C. Jain, Maria Virvou, Vincenzo Piuri, Valentina E. Balas |
| Edizione | [1st ed. 2020.] |
| Pubbl/distr/stampa | Singapore : , : Springer Nature Singapore : , : Imprint : Springer, , 2020 |
| Descrizione fisica | 1 online resource (xix, 262 pages) : illustrations |
| Disciplina | 004 |
| Collana | Advances in Intelligent Systems and Computing |
| Soggetto topico |
Electronic circuits
Signal processing Bioinformatics Multimedia systems Electronic Circuits and Systems Signal, Speech and Image Processing Computational and Systems Biology Multimedia Information Systems |
| ISBN | 981-15-0339-7 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910366604503321 |
| Singapore : , : Springer Nature Singapore : , : Imprint : Springer, , 2020 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
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