Using machine learning to predict deterioration of symptoms in COPD patients within a telemonitoring program.

ABSTRACT: COPD exacerbations have a profound clinical impact on patients. Accurately predicting these events could help healthcare professionals take proactive measures to mitigate their impact. For over a decade, telEPOC, a telehealthcare program, has collected data that can be utilized to train machine learning models to anticipate COPD exacerbations. The objective of this study is to develop a machine learning model that, based on a patient's history, predicts the probability of an exacerbation event within the next 3 days. After cleaning and harmonizing the different subsets of data, we split the data along the temporal axis: one subset for model training, another for model selection, and another for model evaluation. We then trained a gradient tree boosting approach as well as neural network-ba

SUBMITTER: Moraza J 

PROVIDER: S-EPMC11868553 | biostudies-literature | 2025 Feb

REPOSITORIES: biostudies-literature