Obiettivo The aim of the EMG project was to develop a knowledge-based assistant to support physicians in all stages of an electromyographical (EMG) examination of patients with neurological diseases. The objective was to produce a system sufficiently robust to withstand clinical trials in a neurophysiological laboratory. Particular attention was given to involving users in the definition of requirements and in system acceptance testing, and to bringing medical knowledge-based systems to a fully functional state. The aim of the project was to develop a knowledge based assistant to support physicians in all stages of an electromyographical (EMG) examination of patients with neurological diseases. The objective was to produce a system sufficiently robust to withstand clinical trials in a neurophysiological laboratory. Particular attention was given to involving users in the definition of requirements and in system acceptance testing, and to bringing medical knowledge based systems to a fully functional state. The prototype EMG expert system supports the diagnostician in the analysis of EMG signals and advises on the test procedures to be performed. It includes a report generator, and contains a database of case studies. It incorporates a casual probabilistic network model to allow a unified approach to planning, diagnosis, explanation and reporting. The following major features were developed subsequently: robust inference systems; new ways of handling uncertainty by probabilistic methods; and methodologies of general applicability in knowledge representation, blackboard architecture, and user interface specification.The prototype EMG expert system constructed in Phase I supports the diagnostician in the analysis of EMG signals and advises on the test procedures to be performed. It includes a report generator, and contains a database of case studies. It incorporates acausal-probabilistic network model to allow a unified approach to planning, diagnosis, explanation and reporting. Phase II saw a substantial improvement in real-time performance and the development of the following major features: -robust inference systems -new ways of handling uncertainty by probabilistic methods -methodologies of general applicability in knowledge representation, blackboard architecture, and user-interface specification. Exploitation The integrated EMG knowledge-based assistant will broaden the scope of the use of electrophysiological techniques. An expert system shell based on causal-probabilistic reasoning, HUGIN, has been developed and is now available on the market. Campo scientifico natural sciencescomputer and information sciencesdatabasesnatural sciencescomputer and information sciencesknowledge engineeringnatural sciencescomputer and information sciencesartificial intelligenceexpert systems Programma(i) FP1-ESPRIT 1 - European programme (EEC) for research and development in information technologies (ESPRIT), 1984-1988 Argomento(i) Data not available Invito a presentare proposte Data not available Meccanismo di finanziamento Data not available Coordinatore AXION A/S Contributo UE Nessun dato Indirizzo BRENGNOEDVEJ 144 3460 BIRKEROED Danimarca Mostra sulla mappa Costo totale Nessun dato Partecipanti (4) Classifica in ordine alfabetico Classifica per Contributo UE Espandi tutto Riduci tutto Institute of Neurology Regno Unito Contributo UE Nessun dato Indirizzo The National Hospital, Queen Square WC1N 3BG LONDON Mostra sulla mappa Costo totale Nessun dato JUDEX DATASYSTEMER A/S Danimarca Contributo UE Nessun dato Indirizzo LYNGVEJ 8 9000 AALBORG Mostra sulla mappa Costo totale Nessun dato Logica Ltd Regno Unito Contributo UE Nessun dato Indirizzo Betjeman House 104 Hills Road CB2 1LQ Cambridge Mostra sulla mappa Costo totale Nessun dato RESEARCH AND DEVELOPMENT INSTITUTE (NUC) Danimarca Contributo UE Nessun dato Indirizzo FREDRIK BAJERSVEY 7 9220 AALBORG Mostra sulla mappa Costo totale Nessun dato