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Author (up) Blanes-Selva, V.; Ruiz-Garcia, V.; Tortajada, S.; Benedi, J.M.; Valdivieso, B.; Garcia-Gomez, J.M.
Title Design of 1-year mortality forecast at hospital admission: A machine learning approach Type Journal Article
Year 2021 Publication Health Informatics Journal Abbreviated Journal Health Inform. J.
Volume 27 Issue 1 Pages 13pp
Keywords machine learning; palliative care; hospital admission data; mortality forecast
Abstract Palliative care is referred to a set of programs for patients that suffer life-limiting illnesses. These programs aim to maximize the quality of life (QoL) for the last stage of life. They are currently based on clinical evaluation of the risk of 1-year mortality. The main aim of this work is to develop and validate machine-learning-based models to predict the exitus of a patient within the next year using data gathered at hospital admission. Five machine-learning techniques were applied using a retrospective dataset. The evaluation was performed with five metrics computed by a resampling strategy: Accuracy, the area under the ROC curve, Specificity, Sensitivity, and the Balanced Error Rate. All models reported an AUC ROC from 0.857 to 0.91. Specifically, Gradient Boosting Classifier was the best model, producing an AUC ROC of 0.91, a sensitivity of 0.858, a specificity of 0.808, and a BER of 0.1687. Information from standard procedures at hospital admission combined with machine learning techniques produced models with competitive discriminative power. Our models reach the best results reported in the state of the art. These results demonstrate that they can be used as an accurate data-driven palliative care criteria inclusion.
Address [Blanes-Selva, Vicent; Benedi, Jose-Miguel; Garcia-Gomez, Juan M.] Univ Politecn Valencia, Valencia, Spain, Email: viblasel@upv.es
Corporate Author Thesis
Publisher Sage Publications Inc Place of Publication Editor
Language English Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 1460-4582 ISBN Medium
Area Expedition Conference
Notes WOS:000645567000008 Approved no
Is ISI yes International Collaboration no
Call Number IFIC @ pastor @ Serial 5182
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