Sports Medicine

MedFusion-gP-AKI: development and multicenter validation of a machine learning fusion model for early prediction of KDIGO stage 3 acute kidney injury in critically ill traumatic cervicothoracic spinal cord injury patients.

KDIGO stage-3 acute kidney injury (AKI), a life-threatening complication in critically ill patients with traumatic cervicothoracic spinal cord injury (TCTSCI), was associated with a 49.3% 60-day mortality and a median survival of 20 days in a combined MIMIC-IV/eICU analysis, underscoring its severe clinical consequences and the need for early identification and prediction. To address this need, Me...

Application of artificial intelligence in schizophrenia rehabilitation management: a systematic scoping review.

Artificial intelligence (AI) is increasingly used in mental health, yet its rehabilitation-oriented applications in schizophrenia have not been systematically mapped. We conducted a systematic scoping review of PubMed, Web of Science, IEEE Xplore and the ACM Digital Library (January 1, 2012-October 31, 2025; two search rounds), applying operationalized rehabilitation boundaries and excluding diagn...

Utilization of machine learning to identify lower extremity biomechanical predictors of rupture in a validated cadaveric model of ACL injury.

A Piezoionic Hydrogel-Based Electrochemical Strain Sensor for Self-Powered Pulse Monitoring and Machine Learning-Assisted Speech Recognition.

Hydrogel-based strain sensors are attractive for wearable electronics owing to their stretchability, self-healing, and biocompatibility. However, conv...

Machine learning applications for anterior cruciate ligament injury prediction and rehabilitation in sports: A scoping review with evidence synthesis.

PURPOSE: To map and synthesise current evidence on machine learning (ML) applications for anterior cruciate ligament (ACL) injury risk estimation, reh...

Wearable Sleep Measures May Improve Machine Learning Prediction of Home-Based Pulmonary Rehabilitation Engagement Among Patients With Chronic Obstructive Pulmonary Disease: A Proof-of-Concept Study.

OBJECTIVE: To evaluate whether incorporating baseline sleep measures from a wrist-worn activity monitor in machine learning (ML) models improved the p...

Integrating contrastive cross-modal attention and stacked GRU for hand function rehabilitation robot control.

With the intensification of population aging and the increasing incidence of neurological diseases, the demand for precise and intelligent control tec...

Unbiased quantification of persistent postural and motor deficits following spinal cord injury in mice.

Spinal cord injury (SCI) causes multifaceted postural and motor impairments that are challenging to quantify. Conventional behavioral tests, such as t...

Early Prediction of Standing at Discharge in Moderate-to-Severe TBI: A Clinical Machine Learning Model Integrating Modifiable and Nonmodifiable Factors.

OBJECTIVE: To develop and internally validate a machine learning model to predict favorable standing ability at hospital discharge in patients with mo...

Identifying patients at risk for short-term adverse events after hip arthroscopy: a machine learning analysis of a national database.

PURPOSE: To develop and compare machine learning-based risk prediction models to identify patients at risk for short-term adverse outcomes (overnight ...

Bioinspired Keratin-Based Eutectic Hydrogels for Intelligent Health Monitoring and Photothermal Therapy.

The development of epidermal sensors that integrate high mechanical strength, excellent sensing performance, self-healing capability, and monitoring a...

Field Foresight-Predicting the Need for Massive Transfusion, ICU Utilization, and Mechanical Ventilation for Traumatically Injured Patients.

INTRODUCTION: Expeditiously predicting outcomes is essential to allocating blood and intensive care resources. We hypothesize the use of external inju...

A hybrid machine learning approach for predicting traffic accident collision severity.

Accurate prediction of traffic accident severity remains challenging due to feature coupling and class imbalance, which hinder reliable applications i...

Natural Language Processing and Machine Learning Classification Model for Injury Mechanism in Trauma.

INTRODUCTION: Creating and maintaining research databases in trauma can be resource intensive. Natural language processing (NLP) may assist by extract...

Interpretable EEG biomarkers for neurological disease models in mice using bag-of-waves classifiers.

OBJECTIVE: Electroencephalograms (EEGs) are time-series records of the electrical potential from collective neural activity in the brain. EEG waveform...

Early electrocardiographic repolarization changes are associated with subclinical cancer therapy-related cardiac dysfunction in lymphoma patients: A machine learning-assisted longitudinal study.

UNLABELLED: Anthracycline-induced cardiotoxicity remains a significant clinical challenge. We evaluated longitudinal electrocardiographic (ECG) repola...

Automating Virtual Dental Implant Placement: Can AI Match Clinical Expertise?

OBJECTIVES: This study evaluated a validated artificial intelligence (AI) tool for virtual implant planning by comparing its performance with expert-p...

Smart Garment for Continuous Respiration Monitoring in Canines.

There is a growing need for at-home respiration monitoring in canines, who are prone to respiratory issues due to breed-specific anatomy and active li...

Advances in Gait Alterations and Rehabilitation After Anterior Cruciate Ligament Reconstruction: Biomechanics and Emerging Technologies.

Anterior cruciate ligament (ACL) injuries are prevalent in sports and daily life, often leading to functional instability and long-term complications ...

Machine Learning for Estimating Cardiorespiratory Fitness in Patients With Obesity: Protocol for a Retrospective and Prospective Multicenter Cohort Study.

BACKGROUND: Cardiorespiratory fitness (CRF) is a key predictor of cardiovascular and other health-related diseases in individuals with obesity. CRF is...