Does the proposed machine learning approach improve the prediction of unplanned 30-day readmission in ICU patients with heart failure compared to other ML-based models and health calculators?
ICU patients with heart failure
Proposed machine learning approach incorporating time-related variables and medical history from prior hospital visits
Other ML-based models and health calculators
Unplanned 30-day readmission
A novel machine learning approach incorporating time-related variables and prior medical history significantly improves the prediction of 30-day readmission for ICU patients with heart failure.
The proposed approach was capable of modeling the time-related variables and incorporating the medical history of patients from prior hospital visits for prediction. Thus, our approach significantly improved the outcome prediction compared to that of other ML-based models and health calculators.
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Maryam Pishgar
University of Southern California
Julian Theis
University of Illinois Chicago
Marina Del Rios
University of Chicago
SHILAP Revista de lepidopterología
BMC Medical Informatics and Decision Making
University of Iowa
University of Illinois Chicago
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Pishgar et al. (Mon,) studied this question.
synapsesocial.com/papers/69d45800486fe8edee8c8a46 — DOI: https://doi.org/10.1186/s12911-022-01857-y
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