Sports Medicine

Smart assistive technologies for neurodisorders: A review on AI, IoT, and wearable systems for enhanced patient care.

Neurological disorders of the brain and spinal cord affect millions of individuals worldwide and continue to rise in prevalence. Conditions such as Alzheimer's disease, Parkinson's disease, epilepsy, spinal cord injury, and neurodevelopmental disorders disrupt cognitive, motor, and autonomic functions, severely impacting quality of life. This review provides an up-to-date and structured examinatio...

Leveraging Large Language Models for Early Detection of Anomaly Work Injury Cases: Data-Driven Approach to Rehabilitation Efficiency.

BACKGROUND: Large language models (LLMs) have demonstrated potential in automating the analysis of unstructured clinical data, yet their application in rehabilitation therapy for work injury cases remains underexplored. OBJECTIVE: We aimed to evaluate the performance of an LLM-assisted approach for the rapid identification of anomalous rehabilitation cases related to work injuries to enhance scala...

Adversarial robust EEG-based brain-computer interfaces using a hierarchical convolutional neural network.

Brain-Computer Interfaces (BCIs) based on electroencephalography (EEG) are widely used in motor rehabilitation, assistive communication, and neurofeed...

Microbial consortia interactions and bioremediation of pesticides: A review on designing, mechanism and efficacy.

Ecosystems and human health are at serious risk due to the extensive application of pesticides in the agricultural system for controlling pests and di...

Rapid Detection of NDM-Producing Carbapenem-Resistant Escherichia coli Using MALDI-TOF MS Combined with Machine Learning Techniques.

BACKGROUND: Carbapenem-resistant Escherichia coli (CREC) producing New Delhi metallo-beta-lactamase (NDM) poses a substantial threat to global public ...

Behavioral Cloning of Physiotherapists in Adapting Robot Control Parameter.

Robot-aided rehabilitation effectively supports treatment of upper-limb disorders and enhances outcomes when combined with traditional therapy. Artifi...

Predicting Return Home After Moderate-to-Severe Traumatic Brain Injury.

BACKGROUND AND OBJECTIVES: Days alive and at home (DAH) is a validated outcome measure that captures health care transitions between time spent at hom...

Evaluation of diastolic function: Machine learning improves classification of left ventricular filling pressure.

AIMS: Current recommendations for echocardiography-based classification of left ventricular filling pressure (LVFP) as normal or elevated, are based o...

AI-driven low-cost rehabilitation exergame as a lightweight framework for stroke assessment.

Stroke is a leading cause of long-term disability, often affecting upper-limb motor function and requiring continuous assessment. The Fugl-Meyer Asses...

Emerging biosensor and assay-enabled high-throughput screening solutions for enzyme and strain engineering.

High-throughput screening (HTS) platforms and automated biofoundries have enabled large-scale experimentation in enzyme and microbial strain engineeri...

Evaluation of a machine learning system for genomic antimicrobial susceptibility determination on a clinically representative test set.

UNLABELLED: Next-generation sequencing is anticipated to transform infectious disease treatment by enabling faster diagnosis, yet a clinical-grade met...

Mechanoresponsive Biomaterials: Principles, Mechanisms, and Applications.

Mechanoresponsive biomaterials are a revolutionary class of materials designed to respond dynamically to mechanical stimuli, providing tissue engineer...

A Review of Flexible Mechanics Mapping: The Sensing, Transmission, Computation, and Integration Paradigm.

As the sensory foundation for the rapidly evolving era of embodied intelligence and the Internet of Things, Flexible Mechanics Mapping (FMM) is transc...

Multimodal Rehabilitation for Advanced Cancer Pain: a Narrative Review of Emerging Nonpharmacological Strategies.

PURPOSE OF REVIEW: This narrative review aims to explore research advances in multimodal rehabilitation for advanced cancer pain, with a primary focus...

Machine learning models based on adipocyte fatty acid-binding protein help predict the chronic and lethal outcomes of patients with drug-induced liver injury.

PURPOSE: Some patients with drug-induced liver injury (DILI) would progress into chronicity or lethal. Although adipocyte fatty acid-binding protein (...

Optical photothermal infrared (OPTIR) spectroscopy assisted by machine learning for lactic acid bacteria identification at strain level.

Lactic acid bacteria (LAB) are widely used in food, health, and biotechnology sectors, where accurate strain level identification is critical. Convent...

A wearable monitoring system for running gait analysis by diffusion transformer.

Conventional wearable monitoring devices often suffer from insufficient data accuracy and low posture recognition rates, making them inadequate for th...

Deep eutectic hydrogel with polyphenol metal coordination and size reduced cellulose for high performance strain sensing.

Deep eutectic solvent (DES)-based hydrogels are environmentally friendly and structurally tunable, yet their applications are often limited by poor co...

MYO1C is a urinary extracellular vesicle biomarker and mediator of podocyte injury in diabetic nephropathy.

Type 2 diabetic nephropathy (T2DN) is a major complication of type 2 diabetes and a leading cause of chronic kidney disease. This study aimed to explo...

Identifying Key Predictors of Appropriate Discharge Destinations for Older Inpatients in Acute Care: Scoping Review.

BACKGROUND: Postacute care (PAC) services are important to ensure functional recovery and provide adequate care for geriatric inpatients in acute care...