BACKGROUND: The application of machine learning (ML) in predicting the requirement for total knee arthroplasty (TKA) at knee osteoarthritis (KOA) patients has been acknowledged. Nonetheless, the variables employed in the development of ML models are ...
The aim of this study was to determine which items in the psychological assessment forms used by counselling and research centres for individuals with special needs are effective in classifying individuals into special needs diagnostic categories. Da...
Journal of neuroengineering and rehabilitation
Apr 22, 2025
BACKGROUND: Hemiplegic gait after a stroke can result in a decreased gait speed and asymmetrical gait pattern. Normal gait patterns and speed are typically the ultimate goals of gait function in stroke rehabilitation. The purpose of this study was to...
BACKGROUND: Invasive micropapillary carcinoma (IMPC) is a rare subtype of breast cancer characterized by a high risk of lymph node metastasis (LNM). The study aimed to identify predictors of LNM and to develop a machine learning (ML)-based risk predi...
BMC medical informatics and decision making
Apr 22, 2025
OBJECTIVE: To compare the performance of predictive models for cardiovascular event (CVE) in patients undergoing peritoneal dialysis (PD) based on machine learning algorithm and Cox proportional hazard regression.
BACKGROUND: Although gamma Knife radiosurgery (GKRS) is commonly used to treat benign brain tumors, such as meningioma, irradiating the surrounding brain tissue can lead to perifocal edema within a few months after the procedure. Volumetric assessmen...
PURPOSE: The wedge effect (V-effect) is a common complication in intramedullary nailing surgery for intertrochanteric fractures and can significantly affect postoperative outcomes. The purpose of this study was to screen risk factors for the intraope...
BACKGROUND: Objective measures and large datasets are needed to determine aspects of the Clinical Learning Environment (CLE) impacting the essential skill of clinical reasoning documentation. Artificial Intelligence (AI) offers a solution. Here, the ...
BACKGROUND: Healthcare practitioners require a robust predictive system to accurately diagnose diseases, especially in young children with conditions such as anemia. Delays in diagnosis and treatment can have severe consequences, potentially leading ...
BACKGROUND: Hospital readmission following renal transplantation significantly impacts patient outcomes and healthcare resources. While machine learning approaches offer promising solutions for risk prediction, their clinical application often lacks ...
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