Artificial Intelligence
Temporal logics in AI: semantical and ontological considerations
Artificial Intelligence
KARDIO: a study in deep and qualitative knowledge for expert systems
KARDIO: a study in deep and qualitative knowledge for expert systems
Unknown attribute values in induction
Proceedings of the sixth international workshop on Machine learning
Information-Based Evaluation Criterion for Classifier's Performance
Machine Learning
New Generation Computing - Selected papers from the international workshop on algorithmic learning theory,1990
Semi-naive Bayesian classifier
EWSL-91 Proceedings of the European working session on learning on Machine learning
A practical approach to feature selection
ML92 Proceedings of the ninth international workshop on Machine learning
C4.5: programs for machine learning
C4.5: programs for machine learning
Estimating attributes: analysis and extensions of RELIEF
ECML-94 Proceedings of the European conference on machine learning on Machine Learning
Machine learning, neural and statistical classification
Machine learning, neural and statistical classification
A knowledge-based method for temporal abstraction of clinical data
A knowledge-based method for temporal abstraction of clinical data
Data mining and knowledge discovery in databases
Communications of the ACM
The KDD process for extracting useful knowledge from volumes of data
Communications of the ACM
A framework for knowledge-based temporal abstraction
Artificial Intelligence
Deep Models for Medical Knowledge Engineering
Deep Models for Medical Knowledge Engineering
Intelligent Data Analysis in Medicine and Pharmacology
Intelligent Data Analysis in Medicine and Pharmacology
Inductive Logic Programming: Techniques and Applications
Inductive Logic Programming: Techniques and Applications
Machine Learning
Machine Learning
Rule Induction with CN2: Some Recent Improvements
EWSL '91 Proceedings of the European Working Session on Machine Learning
Temporal Abstractions for Diabetic Patients Management
AIME '97 Proceedings of the 6th Conference on Artificial Intelligence in Medicine in Europe
Diagnosis of sport injuries with machine learning: explanation of induced decisions
CBMS '97 Proceedings of the 10th IEEE Symposium on Computer-Based Medical Systems (CBMS '97)
Engineering time in medical knowledge-based systems through time-axes and time-objects
TIME '96 Proceedings of the 3rd Workshop on Temporal Representation and Reasoning (TIME'96)
Dynamic temporal interpretation contexts for temporal abstraction
TIME '96 Proceedings of the 3rd Workshop on Temporal Representation and Reasoning (TIME'96)
Machine learning in prognosis of the femoral neck fracture recovery
Artificial Intelligence in Medicine
Machine Learning for Data Mining in Medicine
AIMDM '99 Proceedings of the Joint European Conference on Artificial Intelligence in Medicine and Medical Decision Making
Application of ILP to Cardiac Arrhythmia Characterization for Chronicle Recognition
ILP '01 Proceedings of the 11th International Conference on Inductive Logic Programming
Incremental application of knowledge to continuously arriving time-oriented data
Journal of Intelligent Information Systems
Intelligent adaptive monitoring for cardiac surveillance
Proceedings of the 2008 conference on ECAI 2008: 18th European Conference on Artificial Intelligence
Data mining for indicators of early mortality in a database of clinical records
Artificial Intelligence in Medicine
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Extensive amounts of knowledge and data stored in medical databases request the development of specialized tools for storing and accessing of data, data analysis, and effective use of stored knowledge and data. This paper focuses on methods and tools for intelligent data analysis, aimed at narrowing the increasing gap between data gathering and data comprehension. The paper sketches the history of research that led to the development of current intelligent data analysis techniques, discusses the need for intelligent data analysis in medicine, and proposes a classification of intelligent data analysis methods. The main scope of the paper are machine learning and temporal abstraction methods and their application in medical diagnosis. A selection of methods and diagnostic domains is presented, and the performance and usefulness of approaches discussed. The paper concludes with the evaluation of selected intelligent data analysis methods and their applicability in medical diagnosis.