Explainable Deep Learning Model for Predicting Serious Adverse Events in Hospitalized Geriatric Patients Within 72 Hours.

Ting-Yu HsuChi-Yung ChengI-Min ChiuChun-Hung Richard LinFu-Jen ChengHsiu-Yung PanYu-Jih SuChao-Jui Li

Published in: Clinical interventions in aging (2024)

The developed DL model demonstrated high accuracy in predicting serious adverse events in geriatric patients within 72 hours of hospitalization. It outperformed the SOFA score and provided valuable insights into the model's decision-making process.

Keyphrases

end stage renal disease
newly diagnosed
deep learning
ejection fraction
chronic kidney disease
decision making
peritoneal dialysis
prognostic factors
patient reported outcomes
convolutional neural network