Latest AI and machine learning research in sports medicine for healthcare professionals.
Background. Deep learning reconstruction (DLR) methods can enhance image quality and reduce scan time of knee MRI compared with conventional approaches but require validation against independent reference standards to ensure robustness and accuracy. Objective. The purpose of this study was to assess the diagnostic performance of a two- to threefold parallel imaging-accelerated 7-minute five-sequen...
OBJECTIVES: Great saphenous vein (GSV) incompetence is common, but numerous treatment options complicate patient-treatment matching. This narrative review synthesizes evidence for major treatment modalities and presents a clinically actionable decision framework integrating clinical, anatomical, and patient-specific factors for precision therapy selection. METHODS: A comprehensive literature searc...
BACKGROUND: Patient-reported outcome measures and healthcare utilization metrics are increasingly used to evaluate the success of total knee arthropla...
PURPOSE: To develop an automated and accurate framework for classifying spinal cord injuries (SCI) and detecting injury levels from CT images, thereby...
OBJECTIVE: Cell-based outer vocal fold replacement (COVR) consists of human adipose-derived stem cells and is a potential treatment for severe vocal f...
Employment is a key social determinant of health, yet people with disabilities (PWDs) face persistent disparities in vocational rehabilitation (VR) se...
Single-level lumbar spinal stenosis (LSS) that does not respond to conservative therapy is now of the standard care given due to minimal invasive deco...
BACKGROUND: The peer review system faces increasing strain from rising manuscript volumes, reviewer fatigue, and well-documented interreviewer disagre...
BACKGROUND: Chronic obstructive pulmonary disease (COPD) is characterized by progressive airflow limitation, chronic airway inflammation, and epitheli...
OBJECTIVE: To investigate whether combining gait, balance, and infrared thermography improves discrimination between individuals with knee osteoarthri...
INTRODUCTION: Digital technologies are increasingly integrated into neurorehabilitation programs for Parkinson's Disease (PD), enabling remote deliver...
Intrinsically stretchable neuromorphic devices (ISNDs) have been widely investigated for intelligent wearable on-device computing. However, convention...
Lattice strain is a key parameter governing the ferroelectric functionality of BaTiO3 (BTO) thin films; however its precise evaluation typically requi...
Cathepsin L (CTSL) is a prominent therapeutic target for kidney injury, yet clinically available CTSL inhibitors remain limited. Here, we developed an...
OBJECTIVE: This study aims to develop an explainable machine learning (ML) framework integrating clinical, imaging, and procedural features for predic...
Hallux Valgus (HV) is a common deformity in runners that reflects altered foot morphology and thereby redistributes mechanical loads along the lower l...
Sepsis is a highly heterogeneous syndrome, and conventional clinical indicators and single biomarkers often fail to capture its biological complexity ...
OBJECTIVE: To systematically compare two generative artificial intelligence (AI) models, ChatGPT and DeepSeek in the rehabilitation management for axi...
BACKGROUND: Post-stroke cognitive impairment (PSCI) is common and disabling, but identifying patients at risk early remains difficult. We developed an...
BACKGROUND: Artificial intelligence (AI) is increasingly reshaping health professions education, but its relationship with students' future career out...