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[null,"1.","Record Nr.",null,"UNINA9910734849103321"]
[null,null,"Autore",null,"Rojas Ignacio"]
[null,null,"Titolo",null,"Bioinformatics and Biomedical Engineering : 10th International Work-Conference, IWBBIO 2023, Meloneras, Gran Canaria, Spain, July 12–14, 2023, Proceedings, Part II / / edited by Ignacio Rojas, Olga Valenzuela, Fernando Rojas Ruiz, Luis Javier Herrera, Francisco Ortuño"]
[null,null,"Pubbl/distr/stampa",null,"Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2023"]
[null,null,"ISBN",null,"3-031-34960-1"]
[null,null,"Edizione",null,"[1st ed. 2023.]"]
[null,null,"Descrizione fisica",null,"1 online resource (520 pages)"]
[null,null,"Collana",null,"Lecture Notes in Bioinformatics, , 2366-6331 ; ; 13920"]
[null,null,"Disciplina",null,"570.285"]
[{"$nulls":4},"610.28"]
[null,null,"Soggetti",null,"Bioinformatics"]
[{"$nulls":4},"Biomedical engineering"]
[{"$nulls":4},"Computer networks"]
[{"$nulls":4},"Engineering - Data processing"]
[{"$nulls":4},"Computational and Systems Biology"]
[{"$nulls":4},"Biomedical Engineering and Bioengineering"]
[{"$nulls":4},"Computer Communication Networks"]
[{"$nulls":4},"Data Engineering"]
[null,null,"Lingua di pubblicazione",null,"Inglese"]
[null,null,"Formato",null,"Materiale a stampa"]
[null,null,null,"Livello bibliografico","Monografia"]
[null,null,"Nota di contenuto",null,"Intro -- Preface -- Organization -- Contents - Part II -- Contents - Part I -- Feature Selection, Extraction, and Data Mining in Bioinformatics -- Agent Based Modeling of Fish Shoal Behavior -- 1 Introduction -- 2 Modeling -- 3 Methods -- 3.1 Multi agents Based Modeling and Simulation -- 4 Results and Discussion -- References -- Entropy Approach of Processing for Fish Acoustic Telemetry Data to Detect Atypical Behavior During Welfare Evaluation -- 1 Introduction -- 1.1 Biotelemetry -- 1.2 Fish Welfare -- 2 Dataset -- 3 Methods -- 4 Results -- 5 Conclusion -- References -- Determining HPV Status in Patients with Oropharyngeal Cancer from 3D CT Images Using Radiomics: Effect of Sampling Methods -- 1 Introduction -- 2 Material and Methods -- 2.1 Data Set -- 2.2 Image Pre-processing -- 2.3 Feature Extraction -- 2.4 Data Pre-processing and Resampling -- 2.5 Feature Selection -- 2.6 Model Training and Evaluation -- 3 Results -- 3.1 Data Pre-processing and Resampling -- 3.2 Feature Extraction -- "]
[{"$nulls":4},"3.3 Feature Selection -- 3.4 Performance Evaluation -- 4 Discussion -- 5 Conclusion -- References -- MetaLLM: Residue-Wise Metal Ion Prediction Using Deep Transformer Model -- 1 Introduction -- 2 Methodology -- 2.1 MetaLLM: Residue-Wise Metal Ion Prediction -- 3 Experiments and Results -- 3.1 Experimental Details -- 3.2 Result Analysis -- 4 Conclusion -- References -- Genome-Phenome Analysis -- Prediction of Functional Effects of Protein Amino Acid Mutations -- 1 Introduction -- 2 Methods -- 2.1 nsSNV Datasets -- 2.2 Protein Mutation Prediction Methodology: The Holdout- nsSNV Algorithm -- 2.3 Consensus Holdout Training and Selection -- 2.4 Extreme Learning Machine -- 2.5 Random Forests -- 3 Results -- 4 Conclusions and Future Directions -- References -- Optimizing Variant Calling for Human Genome Analysis: A Comprehensive Pipeline Approach -- 1 Introduction."]
[{"$nulls":4},"2 Background -- 3 Methods -- 3.1 Reference -- 3.2 Dataset -- 3.3 Quality and Control -- 3.4 Pipeline -- 3.5 Workflow Management and Reproducibility -- 3.6 Benchmarking -- 3.7 Computational Resources -- 4 Results -- 4.1 Different Methods Performance -- 4.2 Computational Time -- 5 Discussion -- 6 Conclusion -- References -- Healthcare and Diseases -- Improving Fetal Health Monitoring: A Review of the Latest Developments and Future Directions -- 1 Introduction -- 2 Methods -- 2.1 Study Design -- 2.2 Search Strategy -- 2.3 Inclusion Criteria -- 2.4 Selection of Studies -- 2.5 Data Analysis -- 3 Result -- 4 Discussion -- 4.1 The Development of Monitoring Devices for Fetal Well-Being -- 4.2 Algorithm for More Accurate Maternal-Fetal FHR Filtering -- 4.3 Fetal Well-Being Indicators -- 4.4 Target Users -- 5 Conclusion -- References -- Deep Learning for Parkinson's Disease Severity Stage Prediction Using a New Dataset -- 1 Introduction -- 2 Related Work -- 3 Materials and Methods -- 3.1 Data Acquisition -- 3.2 Dataset Construction -- 3.3 Data Pre-processing -- 3.4 Proposed LSTM Model -- 4 Experiments -- 5 Conclusion -- References -- Improved Long-Term Forecasting of Emergency Department Arrivals with LSTM-Based Networks -- 1 Introduction -- 2 Materials and Methods -- 2.1 Data Acquisition -- 2.2 Exploration -- 2.3 Analysis Techniques -- 3 Results -- 4 Conclusion -- References -- High-Throughput Genomics: Bioinformatic Tools and Medical Applications -- Targeted Next Generation Sequencing of a Custom Capture Panel to Target Sequence 112 Cancer Related Genes in Breast Cancer Tumors ERBB2 Positive from Lleida (Spain) -- 1 Introduction -- 2 Methods -- 2.1 Breast Cancer Samples -- 2.2 Targeted Sequencing -- 2.3 Data Analysis -- 3 Results -- 3.1 Targeted Sequencing -- 3.2 Gene Signatures -- 4 Discussion -- References."]
[{"$nulls":4},"An Accurate Algorithm for Identifying Mutually Exclusive Patterns on Multiple Sets of Genomic Mutations -- 1 Introduction -- 2 Method -- 2.1 Similarity and Mutual Exclusion Measure -- 2.2 Weighted Probability Search -- 2.3 Algorithm Steps -- 3 Discussion -- 3.1 ME Simulation Principle and Evaluation of Result -- 3.2 The Result and Analysis of ME Simulation Experiment -- 3.3 Ms Simulation Data -- 3.4 Real Datasets -- 4 Comparative Experiments and Results -- 5 Conclusion -- References -- A 20-Year Journey of Tracing the Development of Web Catalogues for Rare Diseases -- 1 Introduction -- 2 Related Work -- 3 Methods -- 3.1 Implementation -- 3.2 Relationship Between Data Sources -- 3.3 Semantic Structure -- 3.4 Data Readers -- 4 Results -- 5 Discussion -- 6 Conclusions -- References -- Unsupervised Investigation of Information Captured in Pathway Activity Score in scRNA-Seq Analysis -- 1 Introduction -- 2 Materials and Methods -- 2.1 Data Acquisition and Pre-processing -- 2.2 Tested Pathway Activity Transformation Algorithms -- 2.3 "]
[{"$nulls":4},"Algorithm's Evaluation -- 3 Results -- 3.1 Cell Type Separation -- 3.2 Clustering Accuracy -- 3.3 Biological Validation -- 4 Conclusions -- References -- Meta-analysis of Gene Activity (MAGA) Contributions and Correlation with Gene Expression, Through GAGAM -- 1 Introduction -- 2 Background -- 2.1 Single-Cell Sequencing Technologies -- 2.2 GAGAM -- 3 Meta-analysis -- 3.1 Peaks Information -- 3.2 Activity-Expression Correlation -- 3.3 Activity-Expression Coherence -- 3.4 Conclusions -- References -- Predicting Papillary Renal Cell Carcinoma Prognosis Using Integrative Analysis of Histopathological Images and Genomic Data -- 1 Introduction -- 2 Materials and Methods -- 2.1 Dataset Overview -- 2.2 Histopathological Image Processing -- 2.3 Gene Coexpression Analysis -- 2.4 Risk Categorization -- 2.5 Prognosis Prediction Model."]
[{"$nulls":4},"3 Results -- 3.1 Patient Characteristics -- 3.2 Prognosis-related Image Features and Co-expression Gene Module Selection -- 3.3 Enrichment Analysis of the Key Gene Modules -- 3.4 Construction and Evaluation of the Integrative Prognostic Model -- 4 Discussion and Conclusion -- References -- Image Visualization and Signal Analysis -- Medical X-ray Image Classification Method Based on Convolutional Neural Networks -- 1 Introduction -- 2 Image Classification Optimization -- 3 Segmentaion of X-ray Image -- 3.1 Conventional Diagnostics and Segmentation Data -- 3.2 Creating and Training a Segmenting Convolutional Network -- 4 Image Reduction and Neural Network Training -- 4.1 Generating of Segmented Images -- 4.2 Active Regions Computation -- 4.3 Analysis of the Segmented Image -- 4.4 Image Reduction -- 4.5 Training of a Classifying Convolutional Neural Network -- 5 Experimental Results and Discussion -- 6 Conclusion -- References -- Digital Breast Tomosynthesis Reconstruction Techniques in Healthcare Systems: A Review -- 1 Introduction -- 2 Tomosynthesis Technology for Breast Imaging -- 2.1 The Advantages of Tomosynthesis Compared to 2D Mammography -- 3 Methods of Reconstruction Phase -- 3.1 The Importance of the Reconstruction Phase in CAD Systems -- 3.2 Back-Projection Algorithms -- 3.3 Transform Algorithms -- 3.4 Algebraic Reconstruction Techniques -- 3.5 Statistical Reconstruction Techniques -- 4 Analysis and Discussions -- 5 Conclusion and Future Works -- References -- BCAnalyzer: A Semi-automated Tool for the Rapid Quantification of Cell Monolayer from Microscopic Images in Scratch Assay -- 1 Introduction -- 2 Materials and Methods -- 2.1 Sample Images Used for the Algorithm Demonstration -- 2.2 Image Set for a Systematic Algorithm Performance Validation -- 3 Software Implementation -- 4 Results and Discussion."]
[{"$nulls":4},"4.1 Prominent Examples of Cell Scratch Assay Analysis for Different Cell Lines -- 4.2 Systematic Algorithm Validation Using Previously Reported Reference Image Sets -- 5 Conclusion -- References -- Color Hippocampus Image Segmentation Using Quantum Inspired Firefly Algorithm and Merging of Channel-Wise Optimums -- 1 Introduction -- 2 Literature Survey -- 3 Proposed Method -- 4 Experimental Setup -- 5 Result and Analysis -- 6 Conclusion -- References -- Breast Cancer Histologic Grade Identification by Graph Neural Network Embeddings -- 1 Introduction -- 2 Related Works -- 3 Materials and Methods -- 3.1 The Used Datasets -- 3.2 Graph Neural Networks -- 3.3 Graph Construction -- 3.4 Experimental Setup -- 4 Results -- 5 Ablation Study -- 6 Conclusions -- References -- A Pilot Study of Neuroaesthetics Based on the Analysis of Electroencephalographic Connectivity Networks in the Visualization of Different Dance Choreography Styles -- 1 Introduction -- 2 Methods of Data Recording and Analysis -- 2.1 Experimental Paradigm -- 2.2 Processing "]
[{"$nulls":4},"and Analysis Methods -- 3 Results -- 4 Discussion -- 5 Conclusions -- References -- Machine Learning in Bioinformatics and Biomedicine -- Ethical Dilemmas, Mental Health, Artificial Intelligence, and LLM-Based Chatbots -- 1 Introduction -- 2 Methodology -- 3 Data Extraction and Analysis Procedure -- 4 Results -- 5 Ethical Analysis -- 6 Conclusions -- 7 LLM Chatbots, Quality of Care, Responsible Research, and Development in Mental Health -- 8 Access, Exclusion, and User Dependence on Chatbots -- 9 Responsibility and Human Supervision of Chatbots -- 10 Regulation and Chatbot Usage Policies -- 11 Limitations of the Present Review -- References -- Cyclical Learning Rates (CLR'S) for Improving Training Accuracies and Lowering Computational Cost -- 1 Introduction -- 2 Experimental Results and Analysis."]
[{"$nulls":4},"2.1 Data Collection, Preprocessing, Model Architecture, and Learning Rates."]
[null,null,null,"Sommario/riassunto","This volume constitutes the proceedings of the 10th International Work-Conference on IWBBIO 2023, held in Meloneras, Gran Canaria, Spain, during July 12-14, 2022. The total of 79 papers presented in the proceedings, was carefully reviewed and selected from 209 submissions. The papers cove the latest ideas and realizations in the foundations, theory, models, and applications for interdisciplinary and multidisciplinary research encompassing disciplines of computer science, mathematics, statistics, biology, bioinformatics, and biomedicine."]