Exercise & Fitness

Free-Living Hip Accelerometry Predicts Frailty Status and 12-Month Frailty Decline in Older Adults

Frailty is a clinical syndrome in older adults characterized by heightened vulnerability to adverse outcomes, yet it remains under-assessed in routine practice due to time-intensive evaluation methods. Wearable accelerometers offer a promising approach for passive, continuous frailty monitoring. We analyzed data from 151 community-dwelling older adults (≥65 years) in the FACE Aging Study who wore ...

Predicting Cardiopulmonary Exercise Testing Performance in Patients Undergoing Transthoracic Echocardiography - An AI Based, Multimodal Model

Transthoracic echocardiography (TTE) is a widely available tool for diagnosing and managing heart failure but has limited predictive value for survival. Cardiopulmonary exercise test (CPET) performance strongly correlates with survival in heart failure patients but is less accessible. We sought to develop an artificial intelligence (AI) algorithm using TTE and electronic medical records to predict...

CLINICAL VALIDATION OF SWAASA ARTIFICIAL INTELLIGENCE PLATFORM USING COUGH SOUNDS FOR SCREENING AND DIAGNOSIS OF RESPIRATORY DISEASES

Analysis of cough sounds have the potential to give a clue regarding the underlying respiratory disease. The Swaasa AI platform using artificial intel...

Longitudinal Prediction of BMI using Explainable AI: Integrating Polygenic Scores, Maternal, Early-Life and Familial Factors

This study aimed to predict body mass index (BMI) trajectories from childhood to early adulthood using explainable artificial intelligence, integratin...

AI-based Hepatic Steatosis Detection and Integrated Hepatic Assessment from Cardiac CT Attenuation Scans Enhances All-cause Mortality Risk Stratification: A Multi-center Study

Hepatic steatosis (HS) is a common cardiometabolic risk factor frequently present but under-diagnosed in patients with suspected or known coronary art...

Polygenic prediction of phenotypes with a neural empirical Bayes approach

Polygenic risk scores (PRS) estimate the expected value of a phenotype based on individual genotypes. Although statistical approaches for calculating ...

A Data-Driven Approach to Polycystic Ovary Syndrome Diagnosis: Evaluating Machine Learning Models

PCOS is recognized as a major health concern affecting women around the world. Early detection and treatment of PCOS significantly reduce implications...

Deep learning predicts cardiac output from seismocardiographic signals in heart failure

Determination of cardiac output (CO) is essential to the clinical management of cardiovascular compromise. However, the invasiveness, procedural risks...

Associations between obstructive sleep apnea and comorbidities in a large clinical biobank

Obstructive sleep apnea (OSA) is associated with a wide range of comorbidities, but large-scale phenome-wide analyses in clinical biobanks remain unde...

Sleep as a Modifiable Risk Factor for Childhood Autism: Stratified Analysis of U.S. National Survey of Children’s Health Data

This study aimed to examine the association between age-specific sleep sufficiency and autism spectrum disorders (ASD) among U.S. children aged 6–17 y...

Risk Prediction Modelling of 30-day all-cause mortality following percutaneous coronary intervention in an Australian population: Leveraging Machine Learning

Pre-procedural risk prediction of 30-day all-cause mortality after percutaneous coronary intervention (PCI) aids in clinical decision-making and bench...

An ensemble method associates prepregnancy BMI and maternal ethnicity with key cord blood metabolomic changes in a multi-ethnic cohort from Hawaii

Maternal obesity poses significant risks to fetal health, influencing metabolomic profiles in newborn cord blood. Despite the growing application of m...

Predicting Olanzapine Induced BMI increase using Machine Learning on population-based Electronic Health Records

Weight gain is a common side effect in patients treated with olanzapine (N05AH03), contributing to increased risks of metabolic complications such as ...

Serum metabolic signatures are associated with anti-drug antibody development in rheumatoid arthritis patients treated with adalimumab

Development of anti-drug antibodies (ADAs) is a barrier to long-term efficacy of biologic therapies in rheumatoid arthritis (RA), but no biomarkers ex...

Assessing the Quality of a Personalized Prompt Generator and AI-Chatbot (ChatGPT) for Dietary and Exercise Planning in Obese Adults Using the Fuzzy Delphi Method

The potential of artificial intelligence (AI) to personalize dietary and exercise advice for obesity management is increasingly evident. However, the ...

Explainable AI to predict a complex multifactorial outcome, childhood obesity: Application to clinical epidemiology

Childhood obesity, driven by genetic and epidemiological factors, poses significant health risks, yet traditional machine learning models lack interpr...

Metabolic Subphenotypes of Obstructive Sleep Apnea: NHANES 2017-2020 (pre-pandemic)

OSA and MetS have a bidirectional relationship but increasing evidence suggests metabolic heterogeneity in OSA, systematic phenotyping of metabolic dr...

Altered microbial carbohydrate metabolism is associated with anxiety and gastrointestinal symptoms in patients with Generalized Anxiety Disorder

Generalized anxiety disorder (GAD) is a common psychiatric condition, with unknown etiology and pathophysiology. Recent studies have suggested alterat...

Personalized AI Prompt Generator and ChatGPT for Weight Loss: Randomized Controlled Trial in Adults with Overweight and Obesity

The global prevalence of overweight and obesity continues escalating, driven by environmental factors and lifestyle behaviors leading to cardiovascula...

Digital phenotyping using wearable-determined physical behaviors and machine learning to detect depression and anxiety in a general population

Depression and anxiety are widespread mental health disorders, yet their diagnosis remains challenging. Digital phenotyping with wearable devices prov...