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Towards a decision support system for hand dermatology
Luca Mazzola1, Alice Cavazzina1, Francesco Pinciroli1
1eHealthLAB, Dipartimento di Elettronica, Informazione e Bioingegneria, Politecnico di Milano, Milan, ITALY.
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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