Artificial Intelligence in Medicine: 10th Conference on Artificial Intelligence in Medicine, AIME 2005, Aberdeen, UK, July 23-27, 2005, ProceedingsSilvia Miksch, Jim Hunter, Elpida Keravnou 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. |
From inside the book
Results 1-5 of 78
Page xvi
... Method for Long-Term Dietary Menu Planning Balázs Gaál, István Vassányi, György Kozmann ................... Human/Computer Interaction to Learn Scenarios from ICU Multivariate Time Series Thomas Guyet, Catherine Garbay, Michel Dojat ...
... Method for Long-Term Dietary Menu Planning Balázs Gaál, István Vassányi, György Kozmann ................... Human/Computer Interaction to Learn Scenarios from ICU Multivariate Time Series Thomas Guyet, Catherine Garbay, Michel Dojat ...
Page 4
... methods. Linguistic Methods are directly rooted in the original record linkage work all the way back to the early 60's. They try to exploit the linguistic labels attached to the concepts in source and target ontology in order to ...
... methods. Linguistic Methods are directly rooted in the original record linkage work all the way back to the early 60's. They try to exploit the linguistic labels attached to the concepts in source and target ontology in order to ...
Page 9
... method used in [5] to identify a set of wood workshop activities using three wearable 3-axis accelerometers and two ... Methods. Context recognition, as defined in ubiquitous and wearable computing, builds on a many methods from classical ...
... method used in [5] to identify a set of wood workshop activities using three wearable 3-axis accelerometers and two ... Methods. Context recognition, as defined in ubiquitous and wearable computing, builds on a many methods from classical ...
Page 14
... method of local trend extraction by determining, during a `Olearning ́O period, the size of the time frame during which the linear approximation of the signal is statistically significant. The transformation allows to decompose each ...
... method of local trend extraction by determining, during a `Olearning ́O period, the size of the time frame during which the linear approximation of the signal is statistically significant. The transformation allows to decompose each ...
Page 15
... methods have different aims. For TrendX or Vie-Vent, the goal is clearly to provide an assistance to medical diagnosis ... method of approximation ? Last, what information should be brought at the medical personnel's attention ? Each of ...
... methods have different aims. For TrendX or Vie-Vent, the goal is clearly to provide an assistance to medical diagnosis ... method of approximation ? Last, what information should be brought at the medical personnel's attention ? Each of ...
Contents
3 | |
23 | |
43 | |
Decision Support Systems | 56 |
Extending Temporal Databases to Deal with TelicAtelic Medical Data | 58 |
An Expert System for Atherosclerosis Risk Assessment | 78 |
A Rehabilitation Expert System for Poststroke Patients | 94 |
A Collaborative Activities Representation for Building | 111 |
The Use of Verbal Classification in Determining the Course of Medical | 276 |
Interactive Knowledge Validation in CBR for Decision Support | 287 |
Adaptation and Medical CaseBased Reasoning Focusing on Endocrine | 300 |
Towards Information Visualization and Clustering Techniques for | 315 |
Automatic Landmarking of Cephalograms by Cellular Neural Networks | 333 |
Morphometry of the Hippocampus Based on a Deformable Model | 353 |
Multiagent Patient Representation in Primary Care | 375 |
Clinical Reasoning Learning with Simulated Patients | 385 |
Improving Clinical Guideline Implementation Through Prototypical | 126 |
Helping Physicians to Organize Guidelines Within Conceptual | 141 |
MHB A ManyHeaded Bridge Between Informal and Formal | 146 |
A HistoryBased Algebra for QualityChecking Medical Guidelines | 161 |
Gaining Process Information from Clinical Practice Guidelines Using | 181 |
Formalising Medical Quality Indicators to Improve Guidelines | 201 |
OntologyMediated Distributed Decision Support for Breast Cancer | 221 |
Building Medical Ontologies Based on Terminology Extraction from | 231 |
Using Lexical and Logical Methods for the Alignment of Medical | 241 |
A Benchmark Evaluation of the French MeSH Indexers | 251 |
Ontology of Time and Situoids in Medical Conceptual Modeling | 266 |
Which Kind of Knowledge Is Suitable for Redesigning Hospital Logistic | 400 |
An Evolutionary Divide and Conquer Method for LongTerm Dietary | 419 |
A Data Preprocessing Method to Increase Efficiency and Accuracy | 434 |
Subgroup Mining for Interactive Knowledge Refinement | 453 |
On Understanding and Assessing Feature Selection Bias | 468 |
Learning Rules from Multisource Data for Cardiac Monitoring | 484 |
Signature Recognition Methods for Identifying Influenza Sequences | 504 |
An Algorithm to Learn Causal Relations Between Genes from Steady | 524 |
Author Index | 545 |
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Artificial Intelligence in Medicine: 10th Conference on Artificial ... Silvia Miksch,Jim Hunter,Elpida Keravnou No preview available - 2005 |
Artificial Intelligence in Medicine: 10th Conference on Artificial ... Silvia Miksch,Jim Hunter,Elpida Keravnou No preview available - 2009 |
Common terms and phrases
Abstract accuracy actions AIME algorithm allergen analysis annotation application approach Artificial Intelligence Asbru automatically Bayesian network Berlin Heidelberg 2005 biomedical cancer Case-Based Reasoning classification clinical guidelines complex Computer concepts constraints corpus CPGs data mining database dataset decision support decision tree defined described detection developed diabetes diagnosis disease domain evaluation example expert extraction feature FiO2 formal function gene graph Heidelberg identified implemented indicators interaction keratoconus knowledge base language machine learning Medical Informatics Medicine method Miksch multi-agent systems multisource n-gram neural network node obtained ontology paper parameters patient patterns performance problem Proc proposed query region predictions relations relevant represent representation rules score selection semantic sequences sketch specific Springer-Verlag Berlin Heidelberg step structure subgroup Support Vector Machines task TeachMed techniques templates temporal therapy threshold tion topological ordering treatment values variables visualization