Latest AI and machine learning research in exercise & fitness for healthcare professionals.
OBJECTIVES: To examine the relationship between cardiorespiratory fitness (CRF) and brain aging, and the extent to which this is mediated by systemic inflammation. METHODS: This study included 4,770 adults from the UK Biobank (mean age: 55.37 ± 7.50 years) at baseline, who underwent structural and functional brain magnetic resonance imaging (MRI) at a follow-up examination conducted an average of...
BACKGROUND: Timely medical follow-up after a diagnosis of cognitive impairment, such as mild cognitive impairment (MCI) or dementia, is imperative for initiating appropriate medical treatment and accessing comprehensive care management and psychosocial support. However, many community-dwelling older adults who receive a positive case-finding result default on their medical follow-up appointments. ...
BACKGROUND: Cardiac rehabilitation (CR) improves functional capacity and outcomes in patients with heart failure (HF). However, a clinically significa...
Diminished drive is one of the core symptoms of major depressive disorder (MDD) diagnosis, yet its underlying neural mechanisms remain elusive, primar...
Personalized data-driven interventions for depression are much needed. Here, we leveraged N-of-1 machine learning (ML) to optimally target behavioral ...
OBJECTIVE: To explore the clinical value of AI-assisted pulmonary rehabilitation education in patients undergoing thoracoscopic surgery for lung cance...
BACKGROUND: Artificial intelligence (AI) has significant potential to improve dermatological care, but most studies have concentrated on image-based s...
Patients with intracerebral hemorrhage (ICH) are at high risk of venous thromboembolism (VTE). Current risk assessment tools are limited and not tailo...
Defining molecular pathways driving β-cell failure in type 2 diabetes (T2D) is challenging given donor heterogeneity. We developed an interpretable ma...
INTRODUCTION: Beauty standards have undergone profound changes over time, with historical depictions of the female body often favoring fuller figures,...
BACKGROUND: The triglyceride-glucose (TyG) index and triglyceride-glucose-body mass index (TyG-BMI) are emerging surrogate markers of insulin resistan...
The objective of this study was to assess ChatGPT's responses to common office ergonomics and spine health questions. ChatGPT was asked the 50 most fr...
This paper conceptualizes emotion regulation (ER) as a dynamic, closed-loop control system composed of three interlinked stages: motivation, execution...
BACKGROUND: Gestational diabetes mellitus (GDM) affects 15-25% of pregnancies worldwide and poses serious risks of macrosomia, preeclampsia, neonatal ...
PURPOSE: To investigate the feasibility of non-invasively identifying bone marrow involvement (BMI) in follicular lymphoma (FL) using baseline 18F-FDG...
This paper presents an algorithmic paradigm that will address a malware model in the form of a nonlinear set of differential equations. The neural net...
AIMS: To develop a machine learning framework for predicting type 2 diabetes mellitus (T2DM) using administrative data and electronic health records (...
Cardio-Vascular Diseases (CvDs) persist as a significant mortality reason worldwide, which requires advanced risk categorization technologies that can...
BACKGROUND: Hypertrophic cardiomyopathy (HCM) is the most common inherited myocardial disorder and a major cause of sudden cardiac death in young adul...
Predicting how mutations affect protein stability and protein-protein binding affinity is crucial for protein engineering and drug development. Althou...