Multimodal Clinical Data Integration for Post-Discharge Risk Stratification: Ensemble Learning Approaches to Hospital Readmission Prediction

Authors

  • Beatriz Hernandez-Gomez Professor of Industrial Engineering, Monterrey Institute of Technology and Higher Education (ITESM)

Keywords:

multimodal clinical data integration, post-discharge risk stratification, ensemble learning approaches to hospital readmission prediction, machine learning

Abstract

1. Introduction Hospital readmissions are a recurring issue that affects millions of people annually across the globe. When patients are sent home before necessary, are unable to afford prescribed drugs, forget to take them, are uninformed about symptoms that necessitate prompt medical attention, or are unable to contact their medical practitioner, the odds of them returning to the hospital increase.

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Published

31-12-2025

How to Cite

[1]
“Multimodal Clinical Data Integration for Post-Discharge Risk Stratification: Ensemble Learning Approaches to Hospital Readmission Prediction”, Adv. in Deep Learning Techniques, vol. 5, no. 2, pp. 19–26, Dec. 2025, Accessed: Jun. 05, 2026. [Online]. Available: https://www.thesciencebrigade.com/adlt/article/view/773