Integration of Current Clinical Knowledge with a Data Driven Approach: An Innovative Perspective

D. Mendes, S. Paredes, T. Rocha, P. Carvalho, J. Henriques and J. Morais
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D. Mendes: CISUC, University of Coimbra, DEI, Polo 2, Pinhal de Marrocos, Coimbra, 3030-290, Portugal
S. Paredes: #x2020;Polytechnic Institute of Coimbra/ISEC, Rua Pedro Nunes — Quinta da Nora, Coimbra, 3030-199, Portugal
T. Rocha: #x2020;Polytechnic Institute of Coimbra/ISEC, Rua Pedro Nunes — Quinta da Nora, Coimbra, 3030-199, Portugal
P. Carvalho: CISUC, University of Coimbra, DEI, Polo 2, Pinhal de Marrocos, Coimbra, 3030-290, Portugal
J. Henriques: CISUC, University of Coimbra, DEI, Polo 2, Pinhal de Marrocos, Coimbra, 3030-290, Portugal
J. Morais: #x2021;Cardiology Department, Leiria Hospital Centre, Ruas das Olhavas, Leiria, 2410-197, Portugal

International Journal of Information Technology & Decision Making (IJITDM), 2018, vol. 17, issue 01, 133-153

Abstract: Cardiovascular diseases are the leading cause of death worldwide. The development of models to support clinical decision is of great importance in the management of these diseases. This work aims to improve the performance exhibited by risk assessment scores that are applied in the clinical practice. This methodology has three main phases: (i) representation of scores as a decision tree; (ii) optimization of the decision tree thresholds using data from recent clinical datasets; (iii) transformation of the optimized decision tree into a new score.This approach was validated in a cardiovascular disease secondary prevention context, supported by a dataset provided by the Portuguese Society of Cardiology (N=13902). The respective performance was assessed using statistical metrics and was compared with GRACE score, the reference in Portuguese clinical practice. The new model originated a better balance between the sensitivity and specificity when compared with the GRACE, originating an accuracy improvement of approximately 22%.

Keywords: Cardiovascular diseases; risk assessment; optimization; knowledge driven process; interpretability (search for similar items in EconPapers)
Date: 2018
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DOI: 10.1142/S0219622017500353

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