Sports Medicine

Preclinical Dialogue Simulation: Evaluating Response Accessibility in Conversational Artificial Intelligence for Aphasia Therapy.

PURPOSE: Large language model (LLM)-driven conversational agents are increasingly considered for use in clinical contexts, yet systematic approaches for evaluating their behavior in impairment-rich, speech-based therapeutic interactions remain limited. This study extends the Agent-Based Conversational Dialogue (ABCD) simulation method as a preclinical testbed to evaluate how LLMs generate accessib...

Predictive value of PfEMP1 antibody profiles for the course of controlled human malaria infections.

Antibody-mediated immunity directed against Plasmodium falciparum erythrocyte membrane protein 1 (PfEMP1) is an important immune mechanism for protection against clinical malaria and control of parasitemia. Current studies on PfEMP1-based immunity are constrained by the protein's high molecular weight, complex multidomain architecture, and extensive polymorphism. Controlled human malaria infection...

Hybrid constitutive law with machine learning for sintering of advanced ceramics.

Predictive simulation of sintering-induced distortion remains challenging for ceramic components subjected to gravity and mechanical constraint. Class...

The application of machine learning in the prediction of sports injuries: systematic review and meta-analysis.

Predicting sports injuries is highly challenging, and current machine learning-based models for predicting sports injuries hold promise for addressing...

CTE has multiple pathologic variants that might relate to different clinical symptom presentation.

Chronic traumatic encephalopathy (CTE) is a progressive neurodegenerative disease found in individuals with a history of repetitive head injury (RHI) ...

GaitNet: Transfer Learning-Enhanced CNN-GRU Architecture for Intention Detection in Healthy and Post-Stroke Participants.

Highly accurate, data-efficient, and real-time detection of human motion intention is essential for the effective control of assistive and rehabilitat...

Computational Insights Into Smart Bioelectronics in Digital Health Care (2020-2024): Topic Modeling Study.

BACKGROUND: Smart bioelectronics are electronic medical devices that combine hardware and artificial intelligence (AI)-based software. These convergen...

Machine Learning-Based Prognostic Models for Functional Outcomes in Spinal Cord Injury: Systematic Review.

BACKGROUND: Machine learning is increasingly used to develop prognostic prediction models for spinal cord injury. Nevertheless, current studies exhibi...

A machine learning framework for multimodal temporal prediction of neurological outcome after out-of-hospital cardiac arrest.

Neurological prognostication after out-of-hospital cardiac arrest (OHCA) remains challenging. Existing clinical scores rely on static, single-timepoin...

A Versatile-Designable Framework for Active and Programmable Shape-Morphing Soft Matter Systems: From Inverse Design to Closed-Loop Control.

Developing soft matter systems with programmability, multifunctional integration, and environmental adaptability represents a critical challenge in so...

Biomechanical phenotypes of 90° change of direction in football players: Unsupervised machine learning in anterior cruciate ligament injury prevention.

PURPOSE: Neuromuscular and biomechanical deficits contribute to anterior cruciate ligament (ACL) injury risk in football. Artificial intelligence (AI)...

AAPM Consensus Guidelines on Neuromodulation Technologies and Neurocomputer Interfaces for Pain Management and Functional Recovery.

OBJECTIVE: To provide an evidence-based framework for healthcare professionals to use neuromodulation technologies to restore neuromuscular function a...

Development of Data-Driven Models for Just-in-Time Digital Self-Management Advice to Improve Physical Functioning in Hip and Knee Osteoarthritis: Protocol for the e-cOAch Cross-Over Study.

BACKGROUND: Clinical guidelines recommend a stepped-care strategy for patients with hip and knee osteoarthritis that begins with nonoperative approach...

Clinical and artificial intelligence assessed echocardiographic predictors of outcomes after acute myocardial infarction.

BACKGROUND: Early risk stratification in patients after acute myocardial infarction (AMI) is critical for guiding therapy and resource allocation. Whi...

Precision neuroprotection in cardiac surgery: a structured narrative review of multimodal, data-driven perioperative care.

Neurological injury remains a major contributor to morbidity, mortality, and long-term cognitive decline in patients undergoing cardiac surgery, despi...

Beyond surgical risk: Multidimensional predictors of postoperative arm morbidity after breast cancer treatment.

BACKGROUND: Postoperative upper-limb morbidity following breast cancer treatment is common and clinically significant, encompassing pain, functional i...

Evaluating the play fighting of rats: A sociological perspective.

BACKGROUND: Play fighting is a prominent social behavior in juvenile rats and is widely used to assess social motivation, affect, and neurobiological ...

Fully automated artificial intelligence-based echocardiographic analysis for global longitudinal strain monitoring and cancer therapy-related cardiac dysfunction detection in breast cancer patients.

AIMS: Global longitudinal strain (GLS) is essential for the early detection of cancer therapy-related cardiac dysfunction (CTRCD). A fully automated e...

Assessing the relevance of biosignal-controlled robotic rehabilitation technologies: a systematic review.

Technology is transforming rehabilitative medicine by enhancing accessibility and personalisation. Robot-assisted rehabilitation uses robotic systems ...

Deep learning-based pressure injury staging: a multicentre study involving 59 hospitals.

BACKGROUND: Accurate assessment of pressure injury staging is essential for guiding appropriate care, reducing patient suffering, alleviating the heal...