Programming in Prolog (2nd ed.)
Programming in Prolog (2nd ed.)
Towards a generalized scheme for QRS detection in ECG waveforms
Signal Processing
Detection of the P and T waves in an ECG
Computers and Biomedical Research
KARDIO: a study in deep and qualitative knowledge for expert systems
KARDIO: a study in deep and qualitative knowledge for expert systems
Learning nonrecursive definitions of relations with LINUS
EWSL-91 Proceedings of the European working session on learning on Machine learning
Artificial Intelligence - Special issue on knowledge representation
Model-based interpretation of the ECG: a methodology for temporal and spatial reasoning
Computers and Biomedical Research - Papers presented at the 16th symposium on computer applications in medical care (SCAMC)
An interactive qualitative model in cardiology
Computers and Biomedical Research
Theories for mutagenicity: a study in first-order and feature-based induction
Artificial Intelligence - Special volume on empirical methods
Inductive logic programming: issues, results and the challenge of learning language in logic
Artificial Intelligence - Special issue on applications of artificial intelligence
Computers and Biomedical Research
A Model-Based Approach for Learning to Identify Cardiac Arrhythmias
AIMDM '99 Proceedings of the Joint European Conference on Artificial Intelligence in Medicine and Medical Decision Making
Machine Learning for Data Mining in Medicine
AIMDM '99 Proceedings of the Joint European Conference on Artificial Intelligence in Medicine and Medical Decision Making
On Multi-class Problems and Discretization in Inductive Logic Programming
ISMIS '97 Proceedings of the 10th International Symposium on Foundations of Intelligent Systems
Learning Structural Knowledge from the ECG
ISMDA '01 Proceedings of the Second International Symposium on Medical Data Analysis
ALT '95 Proceedings of the 6th International Conference on Algorithmic Learning Theory
Analyzing and Learning ECG Waveforms
ILP '96 Selected Papers from the 6th International Workshop on Inductive Logic Programming
Application of ILP to Cardiac Arrhythmia Characterization for Chronicle Recognition
ILP '01 Proceedings of the 11th International Conference on Inductive Logic Programming
An Annotated Data Collection System to Support Intelligent Analysis of Intensive Care Unit Data
IDA '97 Proceedings of the Second International Symposium on Advances in Intelligent Data Analysis, Reasoning about Data
Algorithmic program debugging
Situation recognition: representation and algorithms
IJCAI'93 Proceedings of the 13th international joint conference on Artifical intelligence - Volume 1
On using causal knowledge to recognize vital signals: knowledge-based interpretation of arrhythmias
IJCAI'85 Proceedings of the 9th international joint conference on Artificial intelligence - Volume 1
Artificial neural networks for automatic ECG analysis
IEEE Transactions on Signal Processing
A knowledge-based approach to ECG interpretation using fuzzy logic
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Artificial Intelligence in Medicine
Temporal abstraction in intelligent clinical data analysis: A survey
Artificial Intelligence in Medicine
Automated detection of qualitative spatio-temporal features in electrocardiac activation maps
Artificial Intelligence in Medicine
Fault detection and isolation based on fuzzy automata
Information Sciences: an International Journal
Intelligent adaptive monitoring for cardiac surveillance
Proceedings of the 2008 conference on ECAI 2008: 18th European Conference on Artificial Intelligence
Logic-based representation, reasoning and machine learning for event recognition
Proceedings of the Fourth ACM International Conference on Distributed Event-Based Systems
Learning rules from multisource data for cardiac monitoring
AIME'05 Proceedings of the 10th conference on Artificial Intelligence in Medicine
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This paper proposes a novel approach to cardiac arrhythmia recognition from electrocardiograms (ECGs). ECGs record the electrical activity of the heart and are used to diagnose many heart disorders. The numerical ECG is first temporally abstracted into series of time-stamped events. Temporal abstraction makes use of artificial neural networks to extract interesting waves and their features from the input signals. A temporal reasoner called a chronicle recogniser processes such series in order to discover temporal patterns called chronicles which can be related to cardiac arrhythmias. Generally, it is difficult to elicit an accurate set of chronicles from a doctor. Thus, we propose to learn automatically from symbolic ECG examples the chronicles discriminating the arrhythmias belonging to some specific subset. Since temporal relationships are of major importance, inductive logic programming (ILP) is the tool of choice as it enables first-order relational learning. The approach has been evaluated on real ECGs taken from the MIT-BIH database. The performance of the different modules as well as the efficiency of the whole system is presented. The results are rather good and demonstrate that integrating numerical techniques for low level perception and symbolic techniques for high level classification is very valuable.