Primary Care

Obesity

Latest AI and machine learning research in obesity for healthcare professionals.

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Hybrid Brain-Machine Interface: Integrating EEG and EMG for Reduced Physical Demand

We present a hybrid brain-machine interface (BMI) that integrates steady-state visually evoked pot...

A machine learning approach for Premature Coronary Artery Disease Diagnosis according to Different Ethnicities in Iran

Premature coronary artery disease (PCAD) refers to the early onset of the disease, usually before ...

Transcriptomic profiling and machine learning uncover gene signatures of psoriasis endotypes and disease severity

Despite increased understanding of psoriasis pathogenesis, molecular classification of clinical phen...

DeepDiff-SHAP: Interpretable deep learning for subgroup-specific causal inference using conditional SHAP

Precision medicine aims to tailor healthcare strategies to individual differences in genetic, clinic...

A groove brain-music interface for enhancing individual experience of urge to move

When we listen to music, we often feel a pleasurable urge to move to music, known as groove. While p...

Deterministic dynamics of distributional multi-agent reinforcement learning

Understanding how cognition shapes behavior across contexts remains a fundamental challenge for many...

Brain Age Gap Reduction Following Physical Exercise Mirrors Negative Symptom Improvement in Schizophrenia Spectrum Disorders

Schizophrenia spectrum disorders (SSD) are associated with accelerated brain aging, reflected in an ...

Predicting Hypertension Among HIV Patients on Antiretroviral Therapy in Rural Eastern Cape, South Africa Using Machine Learning

Hypertension continues to be a major challenge in developing countries like South Africa, as it sign...

Large language model-assisted causal machine learning for identifying fatigue-related poor glycated hemoglobin in type 2 diabetes

Fatigue is common but mostly untreated in type 2 diabetes, since it requires a diagnostic workup whi...

AcuKG: a comprehensive knowledge graph for medical acupuncture

This study constructs an acupuncture knowledge graph (AcuKG) to systematically organize and represen...

Cross-platform metabolomics imputation using importance-weighted autoencoders

Metabolomics data are often generated through different analytical platforms and different methods o...

Optimized Feature Selection and Advanced Machine Learning for Stroke Risk Prediction in Revascularized Coronary Artery Disease Patients

Coronary artery disease (CAD) is a leading cause of mortality, with stroke being a major complicatio...

Paving the way for precision treatment of psychiatric symptoms with functional connectivity neurofeedback

Major depressive disorder (MDD) remains challenging to treat, with many patients failing to respond ...

A Combined Predictive and Causal Approach for Neighborhood-Level Diabetes Detection

Develop a neighborhood-level framework using machine learning and causal inference to identify socio...

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