Parenting

Interpretable machine learning for cognitive impairment screening: Development and external validation of a clinical prediction model based on NHANES data.

BACKGROUND: Cognitive impairment in older adults poses a growing public health challenge, yet accessible screening tools remain limited. We aimed to develop and validate an interpretable machine learning model for cognitive impairment prediction by routinely collecting clinical data. METHODS: We analyzed 1061 participants from the U.S. National Health and Nutrition Examination Survey (NHANES 2011-...

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 digital health technologies (DHTs), tools such as telemedicine, smartphone applications, wearable devices, and artificial intelligence (AI) are increasingly integrated into the monitoring, assessment, and follow-up processes for IBD. Drawing on a syn...

The future of psychiatry: Reclaiming relevance in an era of technological and systemic transformation.

Psychiatry currently faces the following four intersecting challenges: technological disruption through artificial intelligence (AI); the loss of excl...

Stage-specific FeS-mediated regulation of Paracoccus denitrificans during carbon consumption by machine learning-assisted comparative proteomics.

Inorganic electron donors improve low C/N wastewater denitrification performance and management. This study used an integrated strategy combining prot...

From Nutritional Epidemiology to Clinical Translation: Machine Learning Uncovers Antioxidant-Driven Prevention Strategies for Mitigating Cardiovascular-Arthritis Multimorbidity.

BACKGROUND: The aim of this study was to construct a machine learning (ML) model to predict the effect of dietary antioxidants on cardiovascular-arthr...

Catassembly Triad: A Catalytic Framework for Enantioselective Chiral Molecular Assembly.

Chiral molecular assembly represents a frontier in creating life-inspired functional materials; yet, a predictive framework for its enantioselective c...

From mechanism to application: Harnessing oxidative stress signaling for innovative food design.

As a central pathological process in aging and chronic diseases, oxidative stress (OS) stems from redox imbalance and propagates cellular damage throu...

From 16S rRNA to deep learning: Evolution of computational approaches in human microbiome studies.

The human microbiome plays a vital role in maintaining physiological balance and influencing immunity, metabolism, and disease development. Over the p...

Genetic and epigenetic determinants of injury risk and recovery in elite athletes: toward precision sports medicine.

Musculoskeletal injuries and interindividual variability in recovery remain critical challenges for sustaining elite athletic performance. Despite adv...

Comparing ChatGPT and DeepSeek for ultra-processed food classification: AI models for nutritional research and dietary assessment.

OBJECTIVES: There is growing evidence linking the consumption of ultra-processed foods (UPFs) to adverse health outcomes. Accurate classification of f...

Developing explainable machine learning models from biochemical and clinical data to predict all-cause and cause-specific mortality in CVD-cancer comorbidity: A longitudinal study based on NHANES.

BACKGROUND: Cardiovascular disease (CVD) and cancer are leading causes of mortality, often coexisting in aging populations. Patients with comorbiditie...

Integrating education-based interventions and machine learning for stunting prevention: A case study in East Lombok, Indonesia.

One of the regions in Indonesia that has the highest prevalence of stunting cases is West Nusa Tenggara, with a percentage of cases almost reaching 12...

Can environmental signals influence dietary Behaviours?The impact of governmental green development attention on dietary diversity among older adults.

Against the backdrop of simultaneous national agendas for green transition and healthy ageing, the nutritional behaviour of older adults is being resh...

Development of advanced lung cancer inflammation index-based machine learning models for predicting stroke and mortality: A comparative and interpretable study.

BACKGROUND: The Advanced Lung Cancer Inflammation Index (ALI) is a novel composite index that enables a more holistic evaluation of inflammation and n...

Building and validating a machine learning model to predict coronary heart disease risk based on non-invasive indicators.

BACKGROUND: Coronary heart disease (CHD) remains a leading global cause of death. Early identification of high-risk individuals and timely interventio...

Using machine learning to predict clinical remission with exclusive enteral nutrition in pediatric Crohn disease.

OBJECTIVES: Exclusive enteral nutrition (EEN) is a first-line treatment for induction of remission in luminal pediatric Crohn disease (pCD). However, ...

Artificial intelligence-guided nutritional therapy in the ICU.

PURPOSE OF REVIEW: Critical care nutrition remains a high-stakes and error-prone domain, particularly given the complex metabolic demands and heteroge...

Artificial intelligence in clinical nutrition. A narrative review.

The rapid integration of Artificial Intelligence (AI) into healthcare, particularly clinical nutrition, holds transformative potential for enhanced di...

3D anatomical atlas of the heads of male and female adult Chamaeleo calyptratus.

The veiled chameleon, Chamaeleo calyptratus, is a model organism in the study of reptile development. The extreme size of its cranial casque relative ...

Integrating multi-omics data for personalized nutrition using knowledge graphs and graph neural networks: A comprehensive review.

This comprehensive review focuses on the use of knowledge graphs and Graph Neural Networks (GNNs) to integrate multi-omics data in the field of person...