Artificial Intelligence in Medicine

TRAMA

This book constitutes the refereed proceedings of the 10th Conference on Artificial Intelligence in Medicine in Europe, AIME 2005, held in Aberdeen, UK in July 2005. The 35 revised full papers and 34 revised short papers presented together with 2 invited contributions were carefully reviewed and selected from 148 submissions. The papers are organized in topical sections on temporal representation and reasoning, decision support systems, clinical guidelines and protocols, ontology and terminology, case-based reasoning, signal interpretation, visual mining, computer vision and imaging, knowledge management, machine learning, knowledge discovery, and data mining.

SOMMARIO

Invited Talks.- Ontology Mapping: A Way Out of the Medical Tower of Babel?.- Human Computer Interaction in Context Aware Wearable Systems.- Temporal Representation and Reasoning.- A New Approach to the Abstraction of Monitoring Data in Intensive Care.- Learning Rules with Complex Temporal Patterns in Biomedical Domains.- Discriminating Exanthematic Diseases from Temporal Patterns of Patient Symptoms.- Probabilistic Abstraction of Multiple Longitudinal Electronic Medical Records.- Using a Bayesian-Network Model for the Analysis of Clinical Time-Series Data.- Data-Driven Analysis of Blood Glucose Management Effectiveness.- Extending Temporal Databases to Deal with Telic/Atelic Medical Data.- Dichotomization of ICU Length of Stay Based on Model Calibration.- Decision Support Systems.- AtherEx: An Expert System for Atherosclerosis Risk Assessment.- Smooth Integration of Decision Support into an Existing Electronic Patient Record.- REPS: A Rehabilitation Expert System for Post-stroke Patients.- Clinical Guidelines and Protocols.- Testing Asbru Guidelines and Protocols for Neonatal Intensive Care.- EORCA: A Collaborative Activities Representation for Building Guidelines from Field Observations.- Design Patterns for Modelling Guidelines.- Improving Clinical Guideline Implementation Through Prototypical Design Patterns.- Automatic Derivation of a Decision Tree to Represent Guideline-Based Therapeutic Strategies for the Management of Chronic Diseases.- Exploiting Decision Theory for Supporting Therapy Selection in Computerized Clinical Guidelines.- Helping Physicians to Organize Guidelines Within Conceptual Hierarchies.- MHB – A Many-Headed Bridge Between Informal and Formal Guideline Representations.- Clinical Guidelines Adaptation: Managing Authoring and Versioning Issues.-Open-Source Publishing of Medical Knowledge for Creation of Computer-Interpretable Guidelines.- A History-Based Algebra for Quality-Checking Medical Guidelines.- The Spock System: Developing a Runtime Application Engine for Hybrid-Asbru Guidelines.- AI Planning Technology as a Component of Computerised Clinical Practice Guidelines.- Gaining Process Information from Clinical Practice Guidelines Using Information Extraction.- Ontology-Driven Extraction of Linguistic Patterns for Modelling Clinical Guidelines.- Formalising Medical Quality Indicators to Improve Guidelines.- Ontology and Terminology.- Oncology Ontology in the NCI Thesaurus.- Ontology-Mediated Distributed Decision Support for Breast Cancer.- Multimedia Data Management to Assist Tissue Microarrays Design.- Building Medical Ontologies Based on Terminology Extraction from Texts: Methodological Propositions.- Translating Biomedical Terms by Inferring Transducers.- Using Lexical and Logical Methods for the Alignment of Medical Terminologies.- Latent Argumentative Pruning for Compact MEDLINE Indexing.- A Benchmark Evaluation of the French MeSH Indexers.- Populating an Allergens Ontology Using Natural Language Processing and Machine Learning Techniques.- Ontology of Time and Situoids in Medical Conceptual Modeling.- The Use of Verbal Classification for Determining the Course of Medical Treatment by Medicinal Herbs.- Case-Based Reasoning, Signal Interpretation, Visual Mining.- Interactive Knowledge Validation in CBR for Decision Support in Medicine.- Adaptation and Medical Case-Based Reasoning Focusing on Endocrine Therapy Support.- Transcranial Magnetic Stimulation (TMS) to Evaluate and Classify Mental Diseases Using Neural Networks.- Towards Information Visualization and Clustering Techniques for MRI Data Sets.- Computer Vision and Imaging.- Electrocardiographic Imaging: Towards Automated Interpretation of Activation Maps.- Automatic Landmarking of Cephalograms by Cellular Neural Networks.- Anatomical Sketch Understanding: Recognizing Explicit and Implicit Structure.- Morphometry of the Hippocampus Based on a Deformable Model and Support Vector Machines.- Automatic Segmentation of Whole-Body Bone Scintigrams as a Preprocessing Step for Computer Assisted Diagnostics.- Knowledge Management.- Multi-agent Patient Representation in Primary Care.- Clinical Reasoning Learning with Simulated Patients.- Implicit Learning System for Teaching the Art of Acute Cardiac Infarction Diagnosis.- Which Kind of Knowledge Is Suitable for Redesigning Hospital Logistic Processes?.- Machine Learning, Knowledge Discovery and Data Mining.- Web Mining Techniques for Automatic Discovery of Medical Knowledge.- Resource Modeling and Analysis of Regional Public Health Care Data by Means of Knowledge Technologies.- An Evolutionary Divide and Conquer Method for Long-Term Dietary Menu Planning.- Human/Computer Interaction to Learn Scenarios from ICU Multivariate Time Series.- Mining Clinical Data: Selecting Decision Support Algorithm for the MET-AP System.- A Data Pre-processing Method to Increase Efficiency and Accuracy in Data Mining.- Rule Discovery in Epidemiologic Surveillance Data Using EpiXCS: An Evolutionary Computation Approach.- Subgroup Mining for Interactive Knowledge Refinement.- Evidence Accumulation to Identify Discriminatory Signatures in Biomedical Spectra.- On Understanding and Assessing Feature Selection Bias.- A Model-Based Approach to Visualizing Classification Decisions for Patient Diagnosis.- Learning Rules from Multisource Data for Cardiac Monitoring.- Effective Confidence Region Prediction Using Probability Forecasters.- Signature Recognition Methods for Identifying Influenza Sequences.- Conquering the Curse of Dimensionality in Gene Expression Cancer Diagnosis: Tough Problem, Simple Models.- An Algorithm to Learn Causal Relations Between Genes from Steady State Data: Simulation and Its Application to Melanoma Dataset.- Relation Mining over a Corpus of Scientific Literature.

ALTRE INFORMAZIONI

• Condizione: Nuovo
• ISBN: 9783540278313
• Collana: Lecture Notes in Computer Science
• Dimensioni: 235 x 155 mm
• Formato: Brossura
• Illustration Notes: XVIII, 550 p.
• Pagine Arabe: 550
• Pagine Romane: xviii