Author:
Alexandru G. Floares
Affiliation:
SAIA - Solutions of Artificial Intelligence Applications; IOCN - Cancer Institute Cluj-Napoca, Artificial Intelligence Department, Romania
Keyword(s):
Clinical decision support systems, Data mining, Artificial intelligence, Chronic hepatitis, Prostate cancer, Biopsy.
Related
Ontology
Subjects/Areas/Topics:
Artificial Intelligence
;
Biomedical Engineering
;
Business Analytics
;
Data Engineering
;
Data Mining
;
Databases and Information Systems Integration
;
Datamining
;
Enterprise Information Systems
;
Expert Systems
;
Health Information Systems
;
Knowledge Engineering and Ontology Development
;
Knowledge-Based Systems
;
Sensor Networks
;
Signal Processing
;
Soft Computing
;
Support for Clinical Decision-Making
;
Symbolic Systems
Abstract:
Clinical Decision Support Systems (CDSS) have the potential to replace painful, invasive, and costly procedures, to optimize medical decisions, improve medical care, and reduce costs. An even better strategy is to make use of a knowledge discovery in data approach, with the aid of artificial intelligence tools. This results in transforming conventional CDSS in Intelligent Clinical Decision Support (i-CDSS). Evolving i-CDSS give to the conventional CDSS the capability of self-modifying their rules set, through supervised learning from patients data. Intelligent and evolving CDSS represent a strong foundation for evidence-based medicine. We proposed a methodology of building i-CDSS and related concepts. These are illustrated with some of our results in liver diseases and prostate cancer, some of them showing the best published performance.