This study investigates the use of machine learning (ML) models combined with a Synthetic Minority Over-sampling Technique (SMOTE) and its variants to predict perioperative pressure injuries (PIs) in an imbalanced dataset. PIs are a significant healt...
BACKGROUND: Residual confounding presents a persistent challenge in observational studies, particularly in high-dimensional settings. High-dimensional proxy adjustment methods, such as the high-dimensional propensity score (hdPS), are widely used to ...
OBJECTIVES: To identify the factors associated with post-stroke depression (PSD) and develop a machine learning predictive model using a large dataset, considering sociodemographic, lifestyle, and clinical factors.
The American journal of geriatric psychiatry : official journal of the American Association for Geriatric Psychiatry
May 1, 2025
BACKGROUND: Primary healthcare institutions find identifying individuals with dementia particularly challenging. This study aimed to develop machine learning models for identifying predictive features of older adults with normal cognition to develop ...
Health information management : journal of the Health Information Management Association of Australia
May 1, 2025
BACKGROUND: Hospital-acquired complications (HACs) have an adverse impact on patient recovery by impeding their path to full recovery and increasing healthcare costs.
BACKGROUND: Colorectal polyps are precancerous diseases of colorectal cancer. Early detection and resection of colorectal polyps can effectively reduce the mortality of colorectal cancer. Endoscopic mucosal resection (EMR) is a common polypectomy pro...
The association between chronic lung diseases (CLDs) and the risk of cardiovascular diseases (CVDs) has been extensively recognized. Nevertheless, conventional approaches for CVD risk evaluation cannot fully capture the risk factors (RFs) related to ...
European journal of pain (London, England)
Mar 1, 2025
BACKGROUND: Recurrence is common in chronic low back pain (CLBP). However, predicting the recurrence risk remains a challenge. The aim is to develop and validate a machine learning tool to predict the recurrence risk in patients with CLBP by using mu...
Join thousands of healthcare professionals staying informed about the latest AI breakthroughs in medicine. Get curated insights delivered to your inbox.