AIMC Topic: Patient Discharge
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Enhancing readmission prediction model in older stroke patients by integrating insight from readiness for hospital discharge: Prospective cohort study.
International journal of medical informatics
Feb 22, 2025
BACKGROUND: The 30-day hospital readmission rate is a key indicator of healthcare quality and system efficiency. This study aimed to develop machine-learning (ML) models to predict unplanned 30-day readmissions in older patients with ischemic stroke ...
Effectiveness of Transformer-Based Large Language Models in Identifying Adverse Drug Reaction Relations from Unstructured Discharge Summaries in Singapore.
Drug safety
Feb 21, 2025
INTRODUCTION: Transformer-based large language models (LLMs) have transformed the field of natural language processing and led to significant advancements in various text processing tasks. However, the applicability of these LLMs in identifying relat...
Machine Learning-Driven Modeling to Predict Postdischarge Venous Thromboembolism After Pancreatectomy for Pancreas Cancer.
Annals of surgical oncology
Feb 20, 2025
BACKGROUND: Postdischarge venous thromboembolism (pdVTE) is a life-threatening complication following resection for pancreatic cancer (PC). While national guidelines recommend extended chemoprophylaxis for all, adherence is low and ranges from 1.5 to...
Adaptable graph neural networks design to support generalizability for clinical event prediction.
Journal of biomedical informatics
Feb 15, 2025
OBJECTIVE: While many machine learning and deep learning-based models for clinical event prediction leverage various data elements from electronic healthcare records such as patient demographics and billing codes, such models face severe challenges w...
Development of clinical decision support for patients older than 65 years with fall-related TBI using artificial intelligence modeling.
PloS one
Feb 3, 2025
BACKGROUND: Older persons comprise most traumatic brain injury (TBI)-related hospitalizations and deaths and are particularly susceptible to fall-induced TBIs. The combination of increased frailty and susceptibility to clinical decline creates a sign...
Development of a machine learning model and a web application for predicting neurological outcome at hospital discharge in spinal cord injury patients.
The spine journal : official journal of the North American Spine Society
Jan 31, 2025
BACKGROUND: Spinal cord injury (SCI) is a devastating condition with profound physical, psychological, and socioeconomic consequences. Despite advances in SCI treatment, accurately predicting functional recovery remains a significant challenge. Conve...
Developing a decision support tool to predict delayed discharge from hospitals using machine learning.
BMC health services research
Jan 11, 2025
BACKGROUND: The growing demand for healthcare services challenges patient flow management in health systems. Alternative Level of Care (ALC) patients who no longer need acute care yet face discharge barriers contribute to prolonged stays and hospital...
The Adelaide Score: prospective implementation of an artificial intelligence system to improve hospital and cost efficiency.
ANZ journal of surgery
Jan 3, 2025
BACKGROUND: The Adelaide Score is an artificial intelligence system that integrates objective vital signs and laboratory tests to predict likelihood of hospital discharge.
Predicting Discharge Destination From Inpatient Rehabilitation Using Machine Learning.
American journal of physical medicine & rehabilitation
Dec 31, 2024
Predicting discharge destination for patients at inpatient rehabilitation facilities is important as it facilitates transitions of care and can improve healthcare resource utilization. This study aims to build on previous studies investigating discha...
Machine Learning Prediction for Postdischarge Falls in Older Adults: A Multicenter Prospective Study.
Journal of the American Medical Directors Association
Dec 30, 2024
OBJECTIVES: The study aimed to develop a machine learning (ML) model to predict early postdischarge falls in older adults using data that are easy to collect in acute care hospitals. This may reduce the burden imposed by complex measures on patients ...
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