Work

Identifying Risk of Readmission After Kidney Transplant Using Electronic Health Records-Based Predictive Analytics

Year: 2025

Type: article

Abstract: Purpose: Nationally, 30-40% of kidney transplant patients are readmitted within 90 days, primarily due to immunosuppressive medication side effects or rejection-related events. Early identification of high-risk patients enables timely interventions. We used an AI-powered predictive analytics approach to assess patient risk factors and predict 90-day readmission risk following kidney transplantation.

Source: American Journal of Transplantation

DOI: 10.1016/j.ajt.2025.07.2359

Authors: S. Al-Awadhi, B. Campbell, A. Gaber, D. Homsy, S. Greenwald, A. Waterman

Institution: Houston Methodist

Language: English

Topic: Machine Learning in Healthcare

Subfield: Artificial Intelligence

Field: Computer Science

Domain: Physical Sciences

SDG: Good health and well-being

Open Access status: hybrid

Estimated APC paid: $4,300