Prevention

Enhancing dietary management and nutritional analysis through deep learning: a multi-model approach for food classification and volume estimation.

Nutrition and diet play pivotal roles in fostering a healthy lifestyle. Effective dietary management requires precise identification and analysis of consumed foods. However, manual tracking is susceptible to inefficiencies and human error. This research work proposes a novel scheme to mitigate these issues by developing a deep learning-based solution. This scheme employs Inception V3 for food clas...

Fully closed-loop systems: can people with type 1 diabetes just do it? Insights from open-source systems.

Automated insulin delivery (AID) systems have significantly advanced diabetes management, progressively reducing user interactions required for optimal glucose management. This review evaluates the current landscape and future potential of AID systems without meal announcement, particularly focusing on real-world insights from open-source AID (OS-AID) technologies. Although commercial AID systems ...

Using large language model-based artificial intelligence (AI) suspects to train strategic use of evidence: Preliminary evidence of transfer to mock suspect interviews.

OBJECTIVE: The strategic use of evidence (SUE) is a technique that aims to improve the ability to differentiate between liars and truth-tellers. Howev...

Morphological characterization of a novel model of steatohepatitis in the FAH-/- pig.

Metabolic dysfunction-associated steatohepatitis (MASH) is a global health care burden. Appropriate large animal models mimicking the main MASH charac...

Co-occurrence patterns and related risk factors of dementia and Parkinson's disease among older adults across 204 countries and territories: a spatial correspondence and systematic analysis.

BACKGROUND: Dementia and Parkinson's disease (PD) are among the most prevalent neurological disorders globally. Most previous research has focused on ...

Trends in health literacy discussions within primary health care research: A topic analysis using machine learning techniques.

OBJECTIVE: To reveal the intellectual framework, research trends, and gaps, and evaluate effective health literacy tools in the field of primary healt...

Artificial intelligence based retinal imaging for cardiovascular risk and statin guidance in retinal vein occlusion.

Mechanism of astaxanthin improving exercise-induced muscle damage: an integrated approach using network pharmacology, molecular dynamics simulation, and experimental validation.

UNLABELLED: This research evaluated the potential mechanisms of ASX on EIMD. The network pharmacology, machine learning, and transcription sequencing ...

Identification of COL8A2, MICAL2, and TNFSF10 as potential biomarkers associated with both exercise response and osteoarthritis: a multi-omics integration study.

UNLABELLED: To identify molecular biomarkers associated with both osteoarthritis (OA) pathology and exercise response through multi-omics integration....

Assessment of AI-generated responses to common pregnancy questions: A blinded expert evaluation.

INTRODUCTION: We conducted a cross-sectional, blinded expert evaluation of AI-generated answers to 22 frequently asked pregnancy questions to characte...

Ultrashort echo time MRI radiomics as a predictor of clinical outcomes in patellar tendinopathy: Insights from a large prospective clinical trial.

PURPOSE: To evaluate the predictive utility of radiomic features extracted from ultrashort echo time (UTE) MRI in comparison to conventional proton de...

Metabolic engineering of Pichia pastoris for high-efficiency production of branched-chain amino acids -enriched single-cell protein.

Branched-chain amino acids (BCAAs), including leucine, isoleucine, and valine, are essential nutrients for animals that must be obtained from the diet...

Inferring high-fat dietary patterns from electronic health record data using machine learning.

OBJECTIVES: Electronic health records (EHRs) rarely capture dietary detail, limiting diet-disease research. We aimed to develop machine learning (ML) ...

Predicting beef diet nutritional composition and intake from rumen metagenomic profiles.

Knowledge of diet composition and intake levels in beef cattle is valuable for post hoc feed traceability and for more accurate modelling of the diet ...

Physical exercise protects cardiovascular fitness in long-term spaceflight: what have we learned?

As space exploration advances into the era of deep space exploration, humanity faces unprecedented challenges in maintaining astronaut health, not onl...

Design and rationale of the WARRIOR ancillary study for coronary CT angiographic analysis.

BACKGROUND: Over 50% of women evaluated for suspected ischemia have no obstructive coronary artery disease (INOCA). Statins, angiotensin converting en...

Inaccurate information regarding cardiovascular disease prevention enabled by generative artificial intelligence.

Inaccurate information regarding cardiovascular disease (CVD) prevention is prevalent on the internet and may influence medical decisions. Artificial ...

Cardiac Rehabilitation for Coronary Artery Disease: Gaps, Digital Models, and the Future of Personalized Prevention.

Cardiovascular disease is the leading cause of global morbidity and mortality, with coronary artery disease representing the primary driver of prematu...

A chalcone-rich extract from licorice root inhibits liver steatosis and fibrosis via regulating PPARα and TGFβ signaling.

BACKGROUND: Metabolic dysfunction-associated steatotic liver disease (MASLD) is a major liver disorder, which seriously affects human health globally....

Advances in the Application of Digital Health Technologies in the Management of Patients With Inflammatory Bowel Disease.

Inflammatory bowel disease (IBD) is a chronic disorder that requires long-term follow-up and individualized management. With the rapid development of ...