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Title: An Artificial Intelligence Approach to Thrombophilia Risk
Authors: Vilhena, João
Vicente, Henrique
Martins, M. Rosário
Grañeda, José
Caldeira, Filomena
Gusmão, Rodrigo
Neves, João
Neves, José
Editors: Information Resources Management Association
Keywords: Thrombophilia
Venous Thromboembolism
Logic Programming
Artificial Neural Networks
Knowledge Representation and Reasoning
Issue Date: 2019
Publisher: IGI Global
Citation: Vilhena, J., Vicente, H., Martins, M.R., Grañeda, J., Caldeira, F., Gusmão, R., Neves, J. & Neves, J., An Artificial Intelligence Approach to Thrombophilia Risk. In Information Resources Management Association Ed., Chronic Illness and Long-Term Care: Breakthroughs in Research and Practice, Vol. I, pp. 161–182, IGI Global, Hershey, USA, 2019.
Abstract: Thrombophilia stands for a genetic or an acquired tendency to hypercoagulable states, frequently as venous thrombosis. Venous thromboembolism, represented mainly by deep venous thrombosis and pulmonary embolism, is often a chronic illness, associated with high morbidity and mortality. Therefore, it is crucial to identify the cause of the disease, the most appropriate treatment, the length of treatment or prevent a thrombotic recurrence. This work will focus on the development of a diagnosis decision support system in terms of a formal agenda built on a Logic Programming approach to knowledge representation and reasoning, complemented with a computational framework based on Artificial Neural Networks. The proposed model has been quite accurate in the assessment of thrombophilia predisposition (accuracy close to 95%). Furthermore, the model classified properly the patients that really presented the pathology, as well as classifying the disease absence (sensitivity and specificity higher than 95%).
ISBN: 9781522571223
Type: bookPart
Appears in Collections:QUI - Publicações - Capítulos de Livros

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