Primary Care

Exercise & Fitness

Latest AI and machine learning research in exercise & fitness for healthcare professionals.

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Decoupling Exploration and Policy Optimization: Uncertainty Guided Tree Search for Hard Exploration

The process of discovery requires active exploration -- the act of collecting new and informative da...

The Effects of AI-Guided Exercise and a Smart Ring on Arterial Stiffness (GONDOR-AS): protocol for a randomized controlled trial

Background: Cardiovascular disease (CVD) prevention is limited by the major challenge of low long-te...

Wearable Foundation Models Should Go Beyond Static Encoders

Wearable foundation models (WFMs), trained on large volumes of data collected by affordable, always-...

Holter-to-Sleep: AI-Enabled Repurposing of Single-Lead ECG for Sleep Phenotyping

Sleep disturbances are tightly linked to cardiovascular risk, yet polysomnography (PSG)-the clinical...

Collaborative Temporal Feature Generation via Critic-Free Reinforcement Learning for Cross-User Sensor-Based Activity Recognition

Human Activity Recognition using wearable inertial sensors is foundational to healthcare monitoring,...

A high-throughput method for measuring fungal growth rate on solid media using automated imaging and deep learning

Measuring the growth rate of filamentous fungi is an essential phenotype assay in fungal biology, en...

PAMG-AT: A Physiological Attention Multi-Graph Model with Adaptive Topology for Stress Detection using Wearable Devices

Stress detection with wearable physiological sensors is vital in digital health and affective comput...

A clinical decision making model for NTSV deliveries

Objective: To evaluate modifiable antepartum and intrapartum factors associated with nulliparous, te...

Improved Classification of Acute Physical Fatigue Using Salivary Proteomic Biomarkers: An Exploratory Study

Introduction: Physical fatigue is a key determinant of operational readiness in the physically deman...

Motivation is Something You Need

This work introduces a novel training paradigm that draws from affective neuroscience. Inspired by t...

A ventral tegmental area GABAergic projection to the ventral pallidum regulates value-based decision making in mice

Activity of the mesolimbic system is essential for adaptive performance of reward-related behaviors....

DELTA: Fortifying Human Biological Resilience with an N=1 Digital Health and Dynamic Biomarker Protocol

Societies are aging rapidly in parallel with the increasingly earlier onset of serious diseases in y...

Genomics link obesity and type 2 diabetes to Alzheimer's disease to unveil novel biological insights

Body mass index (BMI), type 2 diabetes (T2D) and associated cardiometabolic features modify Alzheime...

Likelihood-based fine-tuning of protein language models for few-shot fitness prediction and design

Machine learning models trained on measurements of protein functional properties are widely used to ...

Neuroscience-Inspired Deep Learning Brain-Machine Interface Decoder

Brain machine interfaces (BMIs) aim to decode motor intentions from neural activity to enable direct...

Explainable Machine Learning Framework for Predicting Cardiometabolic Risk Using Meal Timing and Eating Habits

Background- Eating timing and regularity represent new contributors to metabolic health, however, th...

An AI-Native Biofoundry for Autonomous Enzyme Engineering: Integrating Active Learning with Automated Experimentation

The engineering of enzymes with novel functions is a cornerstone of synthetic biology but remains bo...

Targeted saliva multi-omics is a reliable, non-invasive method to capture physiological stress and recovery

Determining physiological stress at high resolution is crucial across diverse settings to enable inf...

Multi-omic deep learning identifies exercise-responsive ageing pathways in humans

Genome-wide association studies of physical activity traits have mapped numerous loci, yet the molec...

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