AIMC Topic: Patient Readmission
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AI Bias and Confounding Risk in Health Feature Engineering for Machine Learning Classification Task.
Studies in health technology and informatics
Aug 7, 2025
Recent advancements in machine learning bring unique opportunities in health fields but also pose considerable challenges. Due to stringent ethical considerations and resource constraints, health data can vary in scope, population coverage, and colle...
A comprehensive review of ICU readmission prediction models: From statistical methods to deep learning approaches.
Artificial intelligence in medicine
Jul 1, 2025
The prediction of Intensive Care Unit (ICU) readmission has become a crucial area of research due to the increasing demand for ICU resources and the need to provide timely interventions to critically ill patients. In recent years, several studies hav...
A Meta-Analysis of the Diagnostic Test Accuracy of Artificial Intelligence for Predicting Emergency Department Revisits.
Journal of medical systems
Jun 16, 2025
The revisit of the emergency department (ED) is a key indicator of emergency care quality. Various strategies have been proposed to reduce ED revisits, including the use of artificial intelligence (AI) models for prediction. However, AI model perform...
New care pathways for supporting transitional care from hospitals to home using AI and personalized digital assistance.
Scientific reports
May 25, 2025
Transitional care may play a vital role in the sustainability of Europe's future healthcare system, offering solutions for relocating patient care from hospital to home, therefore addressing the growing demand for medical care as the population is ag...
Machine Learning-Based Hospital Readmission Prediction: A Comparative Analysis of Speciality-Specific vs. All-Specialities Models.
Studies in health technology and informatics
May 15, 2025
Hospital readmissions are a major challenge for healthcare systems, leading to increased costs and adverse patient outcomes. Predicting which patients are at risk of readmission is critical for improving care and optimizing resource allocation. This ...
Machine learning-based survival models for predicting rehospitalization of older hip fracture patients: a retrospective cohort study.
BMC musculoskeletal disorders
May 8, 2025
PURPOSE: To evaluate machine learning-based survival model roles in predicting rehospitalization after hip fractures to improve reduce the burden on the healthcare system.
Clinical and Social Characterization of Patients Hospitalized for COPD Exacerbation Using Machine Learning Tools.
Archivos de bronconeumologia
May 1, 2025
OBJECTIVE: This study aims to employ machine learning (ML) tools to cluster patients hospitalized for acute exacerbations of chronic obstructive pulmonary disease (COPD) based on their diverse social and clinical characteristics. This clustering is i...
Reducing readmissions in the safety net through AI and automation.
The American journal of managed care
Mar 1, 2025
OBJECTIVES: To implement a technology-based, systemwide readmission reduction initiative in a safety-net health system and evaluate clinical, care equity, and financial outcomes.
Machine learning for adverse event prediction in outpatient parenteral antimicrobial therapy: a scoping review.
The Journal of antimicrobial chemotherapy
Dec 2, 2024
OBJECTIVE: This study aimed to conduct a scoping review of machine learning (ML) techniques in outpatient parenteral antimicrobial therapy (OPAT) for predicting adverse outcomes and to evaluate their validation, implementation and potential barriers ...
Impact of wearable device data and multi-scale entropy analysis on improving hospital readmission prediction.
Journal of the American Medical Informatics Association : JAMIA
Nov 1, 2024
OBJECTIVE: Unplanned readmissions following a hospitalization remain common despite significant efforts to curtail these. Wearable devices may offer help identify patients at high risk for an unplanned readmission.
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