30 days All-Cause Readmission

ECCB 2018 poster.

Abstract Heart failure (HF) is one of the leading causes of hospital admissions in the US. Readmission within 30 days after a HF hospitalization is both a recognized indicator for disease progression and a source of considerable financial burden to the healthcare system. Consequently, the identification of patients at risk for readmission is a key step in improving disease management and patient outcome. In this work, we used a large administrative claims dataset to (1) explore the systematic application of neural network-based models versus logistic regression for predicting 30 days all-cause readmission after discharge from a HF admission, and (2) to examine the additive value of patients’ hospitalization timelines on prediction performance.


ECCB 2018 poster can be downloaded here

Paper got accepted in Scientific Reports - Nature

Ahmed Allam
Senior Researcher

Apparently, this member prefers to keep an air of mystery about them.