ABSTRACT
We implemented a prototype of a decision support system called SIR which has a form of a web-based classification service for diagnostic decision support. The system has the ability to select the most relevant variables and to learn a classification rule, which is guaranteed to be suitable also for high-dimensional measurements. The classification system can be useful for clinicians in primary care to support their decision-making tasks with relevant information extracted from any available clinical study. The implemented prototype was tested on a sample of patients in a cardiological study and performs an information extraction from a high-dimensional set containing both clinical and gene expression data.
Subject(s)
Algorithms , Artificial Intelligence , Decision Support Systems, Clinical , Diagnosis, Computer-Assisted/methods , Internet , Pattern Recognition, Automated/methods , Software , User-Computer InterfaceABSTRACT
EuroMISE Center was established in the year 1994bas the joint workplace of Charles University in Prague and Academy of Sciences of the Czech Republic with the support of the European project focused on higher education in methodology field of healthcare. Nowadays, the EuroMISE Center is working as the joint workplace of five organizations. We describe in more details history and nowadays activities of the EuroMISE Center in the field of research, higher education and e
Subject(s)
Education, Graduate/organization & administration , Medical Informatics/education , Research/organization & administration , Curriculum , Czech Republic , Humans , Medical Informatics/methodsABSTRACT
We present three types of eHealth applications that can enhance quality of clinical decision-making. Formalized electronic medical guidelines are bringing medical knowledge close to clinicians. eHealth tools for evaluation knowledge and competency in a given clinical decision-making problem are demonstrated by systems ExaMe and TECOM. The TECOM system supports training of clinical competence in a given decision-making problems using real clinical cases. The TECOM system estimates the decision-maker abilities using a coefficient of prediction or a classical error rate. Transfer of data and knowledge important for clinical decision-making without language barriers is demonstrated on features of the European Journal for Biomedical Informatics.
