The complexity of the medical diagnosis is faced by practitioners relying mainly on their experiences. This can be acquired during daily practices and on-the-job training. Given the complexity and extensiveness of the subject, supporting tools that include knowledge extracted by highly specialized practitioners can be valuable. In the present work, a Decision Support System (DSS) for hand dermatology was developed based on data coming from a Visit Report Form (VRF). Using a Bayesian approach and factors significance difference over the population average for the case, we demonstrated the potentiality of creating an enhanced VRF that include a diagnoses distribution probability based on the DSS rules applied for the specific patient situation.
Towards a decision support system for hand dermatology / L. Mazzola, A. Cavazzina, F. Pinciroli, S. Bonacina, P.D.M. Pigatto, F. Ayala, O. DE PITÀ, A. Sara MARCEGLIA (STUDIES IN HEALTH TECHNOLOGY AND INFORMATICS). - In: e-Health – For continuity of care : Proceedings of MIE2014 / [a cura di] C. Lovis, B. Séroussi, A. Hasman, L. Pape-Haugaard, O. Saka, S. Kjær Andersen. - [s.l] : IOS press, 2014. - ISBN 9781614994312. - pp. 58-62 (( Intervento presentato al 25. convegno European Medical Informatics Conference tenutosi a Istanbul nel 2014 [10.3233/978-1-61499-432-9-58].
Towards a decision support system for hand dermatology
P.D.M. Pigatto;
2014
Abstract
The complexity of the medical diagnosis is faced by practitioners relying mainly on their experiences. This can be acquired during daily practices and on-the-job training. Given the complexity and extensiveness of the subject, supporting tools that include knowledge extracted by highly specialized practitioners can be valuable. In the present work, a Decision Support System (DSS) for hand dermatology was developed based on data coming from a Visit Report Form (VRF). Using a Bayesian approach and factors significance difference over the population average for the case, we demonstrated the potentiality of creating an enhanced VRF that include a diagnoses distribution probability based on the DSS rules applied for the specific patient situation.
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