Sports Medicine

Urine kidney injury molecule-1 predicts subclinical kidney disease among persons living with HIV initiating tenofovir disoproxil fumarate-based ART in Zambia.

INTRODUCTION: Antiretroviral therapy (ART) increases the life expectancy of persons living with HIV (PLWH), but not without potentially serious adverse effects. Tenofovir disoproxil fumarate (TDF) can cause nephrotoxicity, manifesting as acute kidney injury (AKI) that may persist after treatment discontinuation. Kidney injury biomarkers such as kidney injury molecule-1 (KIM-1), retinol-binding pro...

Machine learning-based interpretation of non-contrast feature tracking strain analysis and T1/T2 mapping for assessing myocardial viability.

Assessing myocardial viability is crucial for managing ischemic heart disease. While late gadolinium enhancement (LGE) cardiovascular magnetic resonance (CMR) is the gold standard for viability evaluation, it has limitations, including contraindications in patients with renal dysfunction and lengthy scan times. This study investigates the potential of non-contrast CMR techniques-feature tracking s...

Major Adverse Kidney Events in Hospitalized Older Patients With Acute Kidney Injury: Machine Learning-Based Model Development and Validation Study.

BACKGROUND: Acute kidney injury (AKI) is a common complication in hospitalized older patients, associated with increased morbidity, mortality, and hea...

Predicting noncontact injuries of professional football players using machine learning.

Noncontact injuries are prevalent among professional football players. Yet, most research on this topic is retrospective, focusing solely on statistic...

Current status, challenges, and prospects of artificial intelligence applications in wound repair theranostics.

Skin injuries caused by physical, pathological, and chemical factors not only compromise appearance and barrier function but can also lead to life-thr...

Predicting Discharge Destination From Inpatient Rehabilitation Using Machine Learning.

Predicting discharge destination for patients at inpatient rehabilitation facilities is important as it facilitates transitions of care and can improv...

Research on multi-label recognition of tongue features in stroke patients based on deep learning.

Stroke has become the leading cause of disability in adults worldwide. Early precise rehabilitation intervention is crucial for the recovery of stroke...

Advanced Technology in a Real-World Rehabilitation Setting: Longitudinal Observational Study on Clinician Adoption and Implementation.

BACKGROUND: Advanced technologies are becoming increasingly accessible in rehabilitation. Current research suggests technology can increase therapy do...

A Bibliometric Review of Brain-Computer Interfaces in Motor Imagery and Steady-State Visually Evoked Potentials for Applications in Rehabilitation and Robotics.

In this paper, a bibliometric review is conducted on brain-computer interfaces (BCI) in non-invasive paradigms like motor imagery (MI) and steady-stat...

Empowering the Sports Scientist with Artificial Intelligence in Training, Performance, and Health Management.

Artificial Intelligence (AI) is transforming the field of sports science by providing unprecedented insights and tools that enhance training, performa...

Hope for the best prepare for the worst: acute kidney disease and catastrophic comorbidities (a case report).

It is evident that Acute Kidney Injury (AKI) is an independent risk factor for both the survival of patients and their kidneys. Here, we present a cas...

Development of Machine-learning Model to Predict Anticoagulant Use and Type in Geriatric Traumatic Brain Injury Using Coagulation Parameters.

This study aimed to investigate the patterns of anticoagulation therapy and coagulation parameters and to develop a prediction model to predict the ty...

Multimodal data-based human motion intention prediction using adaptive hybrid deep learning network for movement challenged person.

Recently, social demands for a good quality of life have increased among the elderly and disabled people. So, biomedical engineers and robotic researc...

Consumer views of functional electrical stimulation and robotic exoskeleton in SCI rehabilitation: A mini review.

BACKGROUND: Functional electrical stimulation (FES) and robotic exoskeletons represent emerging technologies with significant potential for restoring ...

Enhancement on selenium volatilization for phytoremediation: role of plant and soil microbe interaction.

This study aimed at quantifying the potential effects of plant and soil microbial interaction on selenium (Se) volatilization, with the specific objec...

Finding the needle in the haystack of isokinetic knee data: Random Forest modelling improves information about ACLR-related deficiencies.

The difficulties of rehabilitation after anterior cruciate ligament (ACL) injuries, subsequent return-to-sport (RTS) let alone achieving pre-injury pe...

Machine learning for the prediction of mortality in patients with sepsis-associated acute kidney injury: a systematic review and meta-analysis.

BACKGROUND: Predicting mortality in sepsis-related acute kidney injury facilitates early data-driven treatment decisions. Machine learning is predicti...

Development of a Virtual Robot Rehabilitation Training System for Children with Cerebral Palsy: An Observational Study.

This paper presents the development of a robotic system for the rehabilitation and quality of life improvement of children with cerebral palsy (CP). T...

Effect of Ultrasound-Guided Extra-Prevertebral Fascial Suprascapular Nerve and Infraclavicular Brachial Plexus Block on Postoperative Analgesia and Phrenic Nerve Function in Shoulder Arthroscopy: A Pilot Study.

PURPOSE: The suprascapular nerve is situated between the prevertebral fascia and the superficial layer of deep cervical fascia and on the surface of t...

Artificial intelligence tools for engagement prediction in neuromotor disorder patients during rehabilitation.

BACKGROUND: Robot-Assisted Gait Rehabilitation (RAGR) is an established clinical practice to encourage neuroplasticity in patients with neuromotor dis...