Orthopedics

Sports Medicine

Latest AI and machine learning research in sports medicine for healthcare professionals.

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Orthopedics Subcategories: Sports Medicine
Showing 232-252 of 6,957 articles
Enhanced prediction of ventilator-associated pneumonia in patients with traumatic brain injury using advanced machine learning techniques.

Ventilator-associated pneumonia significantly increases morbidity, mortality, and healthcare costs a...

An innovative model based on machine learning and fuzzy logic for tracking lower limb exercises in stroke patients.

Rehabilitation after a stroke is vital for regaining functional abilities. However, a shortage of re...

Digital Technologies and Artificial Intelligence in Cardiac Rehabilitation: A Narrative Review.

PURPOSE: This review explores the role and impact of digital technology in cardiac rehabilitation (C...

Effectiveness of an intelligent weight-bearing rehabilitation robot in enhancing recovery following anterior cruciate ligament reconstruction.

AIM: Orthopedic surgery patients frequently delay early rehabilitation due to postoperative discomfo...

A Deep-Learning Empowered, Real-Time Processing Platform of fNIRS/DOT for Brain Computer Interfaces and Neurofeedback.

Brain-Computer Interfaces (BCI) and Neurofeedback (NFB) approaches, which both rely on real-time mon...

AI and Machine Learning for Precision Medicine in Acute Pancreatitis: A Narrative Review.

Acute pancreatitis (AP) presents a significant clinical challenge due to its wide range of severity,...

Machine learning for risk prediction of acute kidney injury in patients with diabetes mellitus combined with heart failure during hospitalization.

This study aimed to develop a machine learning (ML) model for predicting the risk of acute kidney in...

Modelling fourth-order hyperelasticity in soft solids using physics informed neural networks without labelled data.

Mild traumatic brain injury can result from shear shock wave formation in the brain in the event of ...

The effect of lower limb rehabilitation robot on lower limb -motor function in stroke patients: a systematic review and meta-analysis.

BACKGROUND: The assessment and enhancement of lower limb motor function in hemiplegic patients is of...

Machine learning approaches to injury risk prediction in sport: a scoping review with evidence synthesis.

OBJECTIVE: This study reviewed the current state of machine learning (ML) research for the predictio...

Neurorehabilitation in spinal cord injury: Increased cortical activity through tDCS and robotic gait training.

OBJECTIVE: This study investigates the neurophysiological outcomes of combining robot-assisted gait ...

Evaluation methods of pressure injury stages: A systematic review and meta-analysis.

BACKGROUND: Pressure injury is prevalent in clinical settings and demands precise staging for optima...

Application effect of rehabilitation robots in rehabilitation of limb movement disorders based on neural network algorithms.

With the continuous advancement of computer technology and sensor technology, rehabilitation robots ...

Effects of Robot-Assisted Therapy for Upper Limb Rehabilitation After Stroke: An Umbrella Review of Systematic Reviews.

BACKGROUND: Robotic rehabilitation, which provides a high-intensity, high-frequency therapy to impro...

Multimodal feature fusion machine learning for predicting chronic injury induced by engineered nanomaterials.

Concerns regarding chronic injuries (e.g., fibrosis and carcinogenesis) induced by nanoparticles rai...

Construction of a machine learning-based interpretable prediction model for acute kidney injury in hospitalized patients.

In this observational study, we used data from 59,936 hospitalized adults to construct a model. For ...

Machine Learning to Assist in Managing Acute Kidney Injury in General Wards: Multicenter Retrospective Study.

BACKGROUND: Most artificial intelligence-based research on acute kidney injury (AKI) prediction has ...

Visualized hysteroscopic artificial intelligence fertility assessment system for endometrial injury: an image-deep-learning study.

OBJECTIVE: Asherman's syndrome (AS) is a significant cause of subfertility in women from developing ...

Artificial intelligence-based incisive canal visualization for preventing and detecting post-implant injury, using cone beam computed tomography.

The aim of this study was to clinically validate an artificial intelligence (AI)-based tool for auto...

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