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Artificial Intelligence in Medicine [[electronic resource] ] : 16th Conference on Artificial Intelligence in Medicine, AIME 2017, Vienna, Austria, June 21-24, 2017, Proceedings / / edited by Annette ten Teije, Christian Popow, John H. Holmes, Lucia Sacchi
| Artificial Intelligence in Medicine [[electronic resource] ] : 16th Conference on Artificial Intelligence in Medicine, AIME 2017, Vienna, Austria, June 21-24, 2017, Proceedings / / edited by Annette ten Teije, Christian Popow, John H. Holmes, Lucia Sacchi |
| Edizione | [1st ed. 2017.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2017 |
| Descrizione fisica | 1 online resource (XXV, 369 p. 75 illus.) |
| Disciplina | 610.285 |
| Collana | Lecture Notes in Artificial Intelligence |
| Soggetto topico |
Artificial intelligence
Data mining Mathematical logic Computer programming Programming languages (Electronic computers) Artificial Intelligence Data Mining and Knowledge Discovery Mathematical Logic and Formal Languages Programming Techniques Programming Languages, Compilers, Interpreters |
| ISBN | 3-319-59758-2 |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Intro -- Preface -- Organization -- Invited Talks -- SNOMED CT: The Thorny Way Towards Interoperability of Clinical Routine Data -- Collaborative, Exploratory Question Answering Against Medical Literature -- Contents -- Ontologies and Knowledge Representation -- Studying the Reuse of Content in Biomedical Ontologies: An Axiom-Based Approach -- 1 Introduction -- 2 Methods -- 2.1 Types of Term Reuse in Biomedical Ontologies -- 2.2 Characterisation of Ontologies Based on Reuse -- 2.3 Identification of Hidden Axioms -- 2.4 A Modular Strategy for Increasing the Amount of Knowledge that is Already Being Reused -- 3 Results -- 3.1 Experimental Setup -- 3.2 Analysis of the Reused Terms URIs -- 3.3 Analysis by the Type of Reuse -- 3.4 Analysis of Hidden Axioms and Terms Already Reused -- 4 Discussion and Conclusions -- References -- Ontological Representation of Laboratory Test Observables: Challenges and Perspectives in the SNOMED CT Observable Entity Model Adoption -- Abstract -- 1 Introduction -- 2 Materials and Methods -- 2.1 Terminologies and Ontologies -- 2.2 Lab Test Observable Classification -- 3 Results -- 3.1 ELK Classification Metrics -- 3.2 Lab Test Classification Issue -- 3.3 Representation of Observation Using BTL2 -- 4 Conclusion -- References -- CAREDAS: Context and Activity Recognition Enabling Detection of Anomalous Situation -- 1 Introduction -- 2 Related Work -- 2.1 Anomaly Detection -- 2.2 Markov Logic Network (MLN) -- 3 Contributions -- 4 CAREDAS Knowledge Base -- 4.1 Data Structure Definition -- 4.2 The MLN Model for Anomalous Situation Detection -- 5 CAREDAS Inference Engine -- 5.1 Situation Construction -- 5.2 Dynamic Ground MLN Creation -- 5.3 Rules Weights Calculus -- 5.4 Computation of the Weight of Probabilistic Hidden Predicates -- 6 Experimental Evaluation -- 7 Conclusion and Future Work -- References.
Using Constraint Logic Programming for the Verification of Customized Decision Models for Clinical Guidelines -- Abstract -- 1 Introduction -- 2 Related Work -- 2.1 Customization of CPGs -- 2.2 Automatic Verification and Evaluation of CIGs -- 3 Methods -- 3.1 Two-Layered Contextual Decision Model -- 3.2 Constraint Logic Programming and MiniZinc -- 3.3 Using CLP to Check Properties of Two-Layered Decision Models -- 3.4 Analysis of Property Violations and Revisions of the PROforma Model -- 4 Case Study Example -- 5 Results -- 5.1 A Decision Model for Asthma with the Secondary Personal Domains -- 5.2 Verification and Revision of the Decision Model for Asthma -- 6 Discussion and Conclusions -- References -- Constructing Disease-Centric Knowledge Graphs: A Case Study for Depression (short Version) -- 1 Introduction -- 2 Challenges -- 3 Knowledge Resources and Integration -- 4 Use Cases -- 5 Implementation, Discussion and Conclusion -- References -- Bayesian Methods -- Implementing Guidelines for Causality Assessment of Adverse Drug Reaction Reports: A Bayesian Network Approach -- 1 Introduction -- 2 Materials and Methods -- 2.1 Bayesian Network Model Definition -- 2.2 Evaluation Strategy and Software Used -- 3 Results -- 4 Discussion -- 5 Concluding Remarks -- References -- Bayesian Gaussian Process Classification from Event-Related Brain Potentials in Alzheimer's Disease -- Abstract -- 1 Introduction -- 2 Materials and Methods -- 2.1 Subjects -- 2.2 Assessment of Cognitive Decline and Apolipoprotein E Genotyping -- 2.3 Recording and Pre-processing of Event-Related Potentials -- 2.4 Spatial Synchrony Measures -- 2.5 Spatiotemporal Synchrony Measures -- 2.6 Machine Learning Classifiers -- 3 Results -- 3.1 Prediction of Rapid Cognitive Decline -- 3.2 Apolipoprotein E ε4 Classification -- 4 Summary and Discussion -- Acknowledgment -- References. Data Fusion Approach for Learning Transcriptional Bayesian Networks -- Abstract -- 1 Introduction -- 2 Methods -- 2.1 Reconstruction of CML Transcriptional Regulatory Network -- 2.2 Hybrid Bayesian Network Structure Learning Algorithm -- 3 Results and Discussion -- References -- A Prognostic Model of Glioblastoma Multiforme Using Survival Bayesian Networks -- 1 Introduction -- 2 Conditional Survival Bayesian Networks -- 2.1 Modelling Survival in Bayesian Networks -- 2.2 Learning and Inference -- 3 Experimental Work -- 3.1 Experimental Setup -- 3.2 Results -- 4 Conclusions -- References -- Accurate Bayesian Prediction of Cardiovascular-Related Mortality Using Ambulatory Blood Pressure Measurements -- 1 Introduction -- 2 Related Research -- 3 Experimental Methodology -- 4 Results -- 4.1 Bayesian Classification -- 5 Conclusion -- References -- Temporal Methods -- Modelling Time-Series of Glucose Measurements from Diabetes Patients Using Predictive Clustering Trees -- 1 Introduction -- 2 Predictive Clustering Trees for Time Series Modelling -- 3 Data Description and Experimental Design -- 4 Results -- 5 Conclusions -- References -- Estimation of Sleep Quality by Using Microstructure Profiles -- 1 Introduction -- 2 Data Set Description -- 3 Sleep Features -- 3.1 Hypnogram Features -- 3.2 PSM Based Sleep Features -- 4 Methodology -- 4.1 Feature Selection -- 5 Results and Discussion -- 6 Conclusion -- References -- Combining Multitask Learning and Short Time Series Analysis in Parkinson's Disease Patients Stratification -- 1 Introduction -- 2 Background and Motivation -- 3 The Parkinson's Disease Data Set -- 3.1 PPMI Symptoms Data Sets -- 3.2 PPMI Concomitant Medications Log -- 3.3 Experimental Data Set -- 4 Methodology -- 5 Data Analysis -- 5.1 Results -- 6 Conclusions -- References. Change-Point Detection Method for Clinical Decision Support System Rule Monitoring -- 1 Introduction -- 2 Method -- 2.1 Data Transformation to Stabilize Variance -- 2.2 Seasonal-Trend Decomposition -- 2.3 Likelihood Ratio Statistics -- 2.4 Further Improvements -- 3 Experiments -- 3.1 Experiment Design -- 3.2 Results on Data with Known Change-Points -- 3.3 Results on Data with Simulated Change-Points -- 4 Related Work and Discussion -- 5 Conclusion -- References -- Discovering Discriminative and Interpretable Patterns for Surgical Motion Analysis -- 1 Introduction -- 2 Background -- 3 Method -- 3.1 Symbolic Aggregate ApproXimation (SAX) -- 3.2 Bag of Words Representation of Kinematic Data -- 3.3 Vector Space Model (VSM) -- 3.4 Training and Classifying Kinematic Data -- 4 Experimental Evaluation -- 4.1 Gesture Classification -- 4.2 Skills Classification -- 4.3 Interpretable Patterns Visualization -- 5 Conclusion -- References -- Natural Language Processing -- Automatic Classification of Radiological Reports for Clinical Care -- 1 Introduction -- 2 Background and Related Work -- 3 Data Representation and Annotation -- 3.1 Classification Schema -- 3.2 Data -- 4 Report Classification -- 4.1 Text Processing -- 4.2 Automatic Annotation -- 4.3 Classification -- 4.4 Machine Learning Algorithms -- 5 Evaluation and Discussion -- 6 Conclusion -- References -- Learning Concept-Driven Document Embeddings for Medical Information Search -- 1 Introduction -- 2 On the Semantic Gap Problem in Medical Search -- 3 Model -- 3.1 Problem Formulation -- 3.2 Learning the Concept-Based Representation of Documents -- 3.3 Solving the Optimization Problem -- 4 Experiments -- 4.1 Experimental Setup -- 4.2 Results -- 5 Conclusion and Future Work -- References -- Automatic Identification of Substance Abuse from Social History in Clinical Text -- Abstract -- 1 Introduction. 2 Related Work -- 3 Dataset -- 3.1 Annotation Process -- 3.2 Annotation Statistics -- 4 Methods -- 4.1 Step 1 - Identification of Sentences with Substance Abuse Events -- 4.2 Step 2 - Extraction of Entities for Substance Abuse Events -- 4.3 Step 3 - Event Template Creation -- 5 Results -- 5.1 Performance of Sentence and Entity Extraction Steps on the Training Set -- 5.2 Performance of the Event Extraction Pipeline on the Test Set -- 5.3 Error Analysis -- 6 Conclusion -- References -- Analyzing Perceived Intentions of Public Health-Related Communication on Twitter -- 1 Introduction -- 2 Related Work -- 3 Research Design -- 4 An Intention Taxonomy for Public Tweets -- 5 Discourse Features for Intention Discovery -- 6 Results and Discussion -- 7 Conclusion and Future Work -- References -- Exploring IBM Watson to Extract Meaningful Information from the List of References of a Clinical Practice Guideline -- Abstract -- 1 Introduction -- 2 Methods -- 3 Results -- 4 Discussion and Conclusion -- References -- Recurrent Neural Network Architectures for Event Extraction from Italian Medical Reports -- Abstract -- 1 Introduction -- 2 Materials and Methods -- 2.1 Dataset -- 2.2 The Model -- 2.3 Evaluation Metrics -- 3 Results -- 4 Discussion and Conclusion -- References -- Numerical Eligibility Criteria in Clinical Protocols: Annotation, Automatic Detection and Interpretation -- 1 Introduction -- 2 Material -- 3 Methods -- 4 Results and Discussion -- 5 Conclusion and Future Work -- References -- Enhancing Speech-Based Depression Detection Through Gender Dependent Vowel-Level Formant Features -- 1 Introduction -- 2 Vowel-Level Formant Analysis -- 3 Classification Experiments -- 3.1 Set-Up -- 3.2 Results -- 4 Conclusions -- References -- A Co-occurrence Based MedDRA Terminology Generation: Some Preliminary Results -- 1 Introduction -- 2 Background and Related Work. 3 Methods and Experiments. |
| Record Nr. | UNISA-996466279403316 |
| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2017 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
| ||
Artificial Intelligence in Medicine : 16th Conference on Artificial Intelligence in Medicine, AIME 2017, Vienna, Austria, June 21-24, 2017, Proceedings / / edited by Annette ten Teije, Christian Popow, John H. Holmes, Lucia Sacchi
| Artificial Intelligence in Medicine : 16th Conference on Artificial Intelligence in Medicine, AIME 2017, Vienna, Austria, June 21-24, 2017, Proceedings / / edited by Annette ten Teije, Christian Popow, John H. Holmes, Lucia Sacchi |
| Edizione | [1st ed. 2017.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2017 |
| Descrizione fisica | 1 online resource (XXV, 369 p. 75 illus.) |
| Disciplina | 610.285 |
| Collana | Lecture Notes in Artificial Intelligence |
| Soggetto topico |
Artificial intelligence
Data mining Mathematical logic Computer programming Programming languages (Electronic computers) Artificial Intelligence Data Mining and Knowledge Discovery Mathematical Logic and Formal Languages Programming Techniques Programming Languages, Compilers, Interpreters |
| ISBN | 3-319-59758-2 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Intro -- Preface -- Organization -- Invited Talks -- SNOMED CT: The Thorny Way Towards Interoperability of Clinical Routine Data -- Collaborative, Exploratory Question Answering Against Medical Literature -- Contents -- Ontologies and Knowledge Representation -- Studying the Reuse of Content in Biomedical Ontologies: An Axiom-Based Approach -- 1 Introduction -- 2 Methods -- 2.1 Types of Term Reuse in Biomedical Ontologies -- 2.2 Characterisation of Ontologies Based on Reuse -- 2.3 Identification of Hidden Axioms -- 2.4 A Modular Strategy for Increasing the Amount of Knowledge that is Already Being Reused -- 3 Results -- 3.1 Experimental Setup -- 3.2 Analysis of the Reused Terms URIs -- 3.3 Analysis by the Type of Reuse -- 3.4 Analysis of Hidden Axioms and Terms Already Reused -- 4 Discussion and Conclusions -- References -- Ontological Representation of Laboratory Test Observables: Challenges and Perspectives in the SNOMED CT Observable Entity Model Adoption -- Abstract -- 1 Introduction -- 2 Materials and Methods -- 2.1 Terminologies and Ontologies -- 2.2 Lab Test Observable Classification -- 3 Results -- 3.1 ELK Classification Metrics -- 3.2 Lab Test Classification Issue -- 3.3 Representation of Observation Using BTL2 -- 4 Conclusion -- References -- CAREDAS: Context and Activity Recognition Enabling Detection of Anomalous Situation -- 1 Introduction -- 2 Related Work -- 2.1 Anomaly Detection -- 2.2 Markov Logic Network (MLN) -- 3 Contributions -- 4 CAREDAS Knowledge Base -- 4.1 Data Structure Definition -- 4.2 The MLN Model for Anomalous Situation Detection -- 5 CAREDAS Inference Engine -- 5.1 Situation Construction -- 5.2 Dynamic Ground MLN Creation -- 5.3 Rules Weights Calculus -- 5.4 Computation of the Weight of Probabilistic Hidden Predicates -- 6 Experimental Evaluation -- 7 Conclusion and Future Work -- References.
Using Constraint Logic Programming for the Verification of Customized Decision Models for Clinical Guidelines -- Abstract -- 1 Introduction -- 2 Related Work -- 2.1 Customization of CPGs -- 2.2 Automatic Verification and Evaluation of CIGs -- 3 Methods -- 3.1 Two-Layered Contextual Decision Model -- 3.2 Constraint Logic Programming and MiniZinc -- 3.3 Using CLP to Check Properties of Two-Layered Decision Models -- 3.4 Analysis of Property Violations and Revisions of the PROforma Model -- 4 Case Study Example -- 5 Results -- 5.1 A Decision Model for Asthma with the Secondary Personal Domains -- 5.2 Verification and Revision of the Decision Model for Asthma -- 6 Discussion and Conclusions -- References -- Constructing Disease-Centric Knowledge Graphs: A Case Study for Depression (short Version) -- 1 Introduction -- 2 Challenges -- 3 Knowledge Resources and Integration -- 4 Use Cases -- 5 Implementation, Discussion and Conclusion -- References -- Bayesian Methods -- Implementing Guidelines for Causality Assessment of Adverse Drug Reaction Reports: A Bayesian Network Approach -- 1 Introduction -- 2 Materials and Methods -- 2.1 Bayesian Network Model Definition -- 2.2 Evaluation Strategy and Software Used -- 3 Results -- 4 Discussion -- 5 Concluding Remarks -- References -- Bayesian Gaussian Process Classification from Event-Related Brain Potentials in Alzheimer's Disease -- Abstract -- 1 Introduction -- 2 Materials and Methods -- 2.1 Subjects -- 2.2 Assessment of Cognitive Decline and Apolipoprotein E Genotyping -- 2.3 Recording and Pre-processing of Event-Related Potentials -- 2.4 Spatial Synchrony Measures -- 2.5 Spatiotemporal Synchrony Measures -- 2.6 Machine Learning Classifiers -- 3 Results -- 3.1 Prediction of Rapid Cognitive Decline -- 3.2 Apolipoprotein E ε4 Classification -- 4 Summary and Discussion -- Acknowledgment -- References. Data Fusion Approach for Learning Transcriptional Bayesian Networks -- Abstract -- 1 Introduction -- 2 Methods -- 2.1 Reconstruction of CML Transcriptional Regulatory Network -- 2.2 Hybrid Bayesian Network Structure Learning Algorithm -- 3 Results and Discussion -- References -- A Prognostic Model of Glioblastoma Multiforme Using Survival Bayesian Networks -- 1 Introduction -- 2 Conditional Survival Bayesian Networks -- 2.1 Modelling Survival in Bayesian Networks -- 2.2 Learning and Inference -- 3 Experimental Work -- 3.1 Experimental Setup -- 3.2 Results -- 4 Conclusions -- References -- Accurate Bayesian Prediction of Cardiovascular-Related Mortality Using Ambulatory Blood Pressure Measurements -- 1 Introduction -- 2 Related Research -- 3 Experimental Methodology -- 4 Results -- 4.1 Bayesian Classification -- 5 Conclusion -- References -- Temporal Methods -- Modelling Time-Series of Glucose Measurements from Diabetes Patients Using Predictive Clustering Trees -- 1 Introduction -- 2 Predictive Clustering Trees for Time Series Modelling -- 3 Data Description and Experimental Design -- 4 Results -- 5 Conclusions -- References -- Estimation of Sleep Quality by Using Microstructure Profiles -- 1 Introduction -- 2 Data Set Description -- 3 Sleep Features -- 3.1 Hypnogram Features -- 3.2 PSM Based Sleep Features -- 4 Methodology -- 4.1 Feature Selection -- 5 Results and Discussion -- 6 Conclusion -- References -- Combining Multitask Learning and Short Time Series Analysis in Parkinson's Disease Patients Stratification -- 1 Introduction -- 2 Background and Motivation -- 3 The Parkinson's Disease Data Set -- 3.1 PPMI Symptoms Data Sets -- 3.2 PPMI Concomitant Medications Log -- 3.3 Experimental Data Set -- 4 Methodology -- 5 Data Analysis -- 5.1 Results -- 6 Conclusions -- References. Change-Point Detection Method for Clinical Decision Support System Rule Monitoring -- 1 Introduction -- 2 Method -- 2.1 Data Transformation to Stabilize Variance -- 2.2 Seasonal-Trend Decomposition -- 2.3 Likelihood Ratio Statistics -- 2.4 Further Improvements -- 3 Experiments -- 3.1 Experiment Design -- 3.2 Results on Data with Known Change-Points -- 3.3 Results on Data with Simulated Change-Points -- 4 Related Work and Discussion -- 5 Conclusion -- References -- Discovering Discriminative and Interpretable Patterns for Surgical Motion Analysis -- 1 Introduction -- 2 Background -- 3 Method -- 3.1 Symbolic Aggregate ApproXimation (SAX) -- 3.2 Bag of Words Representation of Kinematic Data -- 3.3 Vector Space Model (VSM) -- 3.4 Training and Classifying Kinematic Data -- 4 Experimental Evaluation -- 4.1 Gesture Classification -- 4.2 Skills Classification -- 4.3 Interpretable Patterns Visualization -- 5 Conclusion -- References -- Natural Language Processing -- Automatic Classification of Radiological Reports for Clinical Care -- 1 Introduction -- 2 Background and Related Work -- 3 Data Representation and Annotation -- 3.1 Classification Schema -- 3.2 Data -- 4 Report Classification -- 4.1 Text Processing -- 4.2 Automatic Annotation -- 4.3 Classification -- 4.4 Machine Learning Algorithms -- 5 Evaluation and Discussion -- 6 Conclusion -- References -- Learning Concept-Driven Document Embeddings for Medical Information Search -- 1 Introduction -- 2 On the Semantic Gap Problem in Medical Search -- 3 Model -- 3.1 Problem Formulation -- 3.2 Learning the Concept-Based Representation of Documents -- 3.3 Solving the Optimization Problem -- 4 Experiments -- 4.1 Experimental Setup -- 4.2 Results -- 5 Conclusion and Future Work -- References -- Automatic Identification of Substance Abuse from Social History in Clinical Text -- Abstract -- 1 Introduction. 2 Related Work -- 3 Dataset -- 3.1 Annotation Process -- 3.2 Annotation Statistics -- 4 Methods -- 4.1 Step 1 - Identification of Sentences with Substance Abuse Events -- 4.2 Step 2 - Extraction of Entities for Substance Abuse Events -- 4.3 Step 3 - Event Template Creation -- 5 Results -- 5.1 Performance of Sentence and Entity Extraction Steps on the Training Set -- 5.2 Performance of the Event Extraction Pipeline on the Test Set -- 5.3 Error Analysis -- 6 Conclusion -- References -- Analyzing Perceived Intentions of Public Health-Related Communication on Twitter -- 1 Introduction -- 2 Related Work -- 3 Research Design -- 4 An Intention Taxonomy for Public Tweets -- 5 Discourse Features for Intention Discovery -- 6 Results and Discussion -- 7 Conclusion and Future Work -- References -- Exploring IBM Watson to Extract Meaningful Information from the List of References of a Clinical Practice Guideline -- Abstract -- 1 Introduction -- 2 Methods -- 3 Results -- 4 Discussion and Conclusion -- References -- Recurrent Neural Network Architectures for Event Extraction from Italian Medical Reports -- Abstract -- 1 Introduction -- 2 Materials and Methods -- 2.1 Dataset -- 2.2 The Model -- 2.3 Evaluation Metrics -- 3 Results -- 4 Discussion and Conclusion -- References -- Numerical Eligibility Criteria in Clinical Protocols: Annotation, Automatic Detection and Interpretation -- 1 Introduction -- 2 Material -- 3 Methods -- 4 Results and Discussion -- 5 Conclusion and Future Work -- References -- Enhancing Speech-Based Depression Detection Through Gender Dependent Vowel-Level Formant Features -- 1 Introduction -- 2 Vowel-Level Formant Analysis -- 3 Classification Experiments -- 3.1 Set-Up -- 3.2 Results -- 4 Conclusions -- References -- A Co-occurrence Based MedDRA Terminology Generation: Some Preliminary Results -- 1 Introduction -- 2 Background and Related Work. 3 Methods and Experiments. |
| Record Nr. | UNINA-9910484595103321 |
| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2017 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Artificial Intelligence in Medicine [[electronic resource] ] : 15th Conference on Artificial Intelligence in Medicine, AIME 2015, Pavia, Italy, June 17-20, 2015. Proceedings / / edited by John H. Holmes, Riccardo Bellazzi, Lucia Sacchi, Niels Peek
| Artificial Intelligence in Medicine [[electronic resource] ] : 15th Conference on Artificial Intelligence in Medicine, AIME 2015, Pavia, Italy, June 17-20, 2015. Proceedings / / edited by John H. Holmes, Riccardo Bellazzi, Lucia Sacchi, Niels Peek |
| Edizione | [1st ed. 2015.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2015 |
| Descrizione fisica | 1 online resource (XVI, 345 p. 76 illus.) |
| Disciplina | 519.5 |
| Collana | Lecture Notes in Artificial Intelligence |
| Soggetto topico |
Artificial intelligence
Health informatics Data mining Pattern recognition Application software Artificial Intelligence Health Informatics Data Mining and Knowledge Discovery Pattern Recognition Information Systems Applications (incl. Internet) |
| ISBN | 3-319-19551-4 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Process mining and phenotyping -- Data mining and machine learning -- Temporal data mining -- Uncertainty and Bayesian networks -- Text mining -- Prediction in clinical practice.- Knowledge representation and guidelines. |
| Record Nr. | UNISA-996198524303316 |
| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2015 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
| ||
Artificial Intelligence in Medicine : 15th Conference on Artificial Intelligence in Medicine, AIME 2015, Pavia, Italy, June 17-20, 2015. Proceedings / / edited by John H. Holmes, Riccardo Bellazzi, Lucia Sacchi, Niels Peek
| Artificial Intelligence in Medicine : 15th Conference on Artificial Intelligence in Medicine, AIME 2015, Pavia, Italy, June 17-20, 2015. Proceedings / / edited by John H. Holmes, Riccardo Bellazzi, Lucia Sacchi, Niels Peek |
| Edizione | [1st ed. 2015.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2015 |
| Descrizione fisica | 1 online resource (XVI, 345 p. 76 illus.) |
| Disciplina | 519.5 |
| Collana | Lecture Notes in Artificial Intelligence |
| Soggetto topico |
Artificial intelligence
Health informatics Data mining Pattern recognition Application software Artificial Intelligence Health Informatics Data Mining and Knowledge Discovery Pattern Recognition Information Systems Applications (incl. Internet) |
| ISBN | 3-319-19551-4 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Process mining and phenotyping -- Data mining and machine learning -- Temporal data mining -- Uncertainty and Bayesian networks -- Text mining -- Prediction in clinical practice.- Knowledge representation and guidelines. |
| Record Nr. | UNINA-9910484732703321 |
| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2015 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||