Parenting

Hitchhikers Guide To Training More General Machine Learning Potentials in Heterogeneous Catalysis.

Machine learning potentials (MLPs) have emerged as powerful simulation tools for heterogeneous catalysis. While current MD-active-learning workflows excel at fitting a specific system/reaction pathway through iterative structural sampling, the transition toward more general and transferable MLPs, designed to handle diverse structures and reactive events within a defined chemical space, presents fu...

A Cross-Sectional Study Based on Deep Learning to Explore the Effect of Triglyceride/Glucose Index on Periodontitis: An Analysis Based on the Large NHANES Database.

PURPOSE: Periodontitis is a common chronic inflammatory disease closely associated with metabolic syndrome. The triglyceride-glucose (TyG) index is a surrogate marker of insulin resistance. However, its relationship with periodontitis remains underexplored. This study aims to utilise the large national database (NHANES) and explore the predictive value of TyG index for periodontitis through a deep...

Proteomics-driven innovations in plant-based foods: Current advances, emerging technologies, and future perspectives.

Despite rapid market growth, plant-based foods such as meat analogs, plant-based milk, yogurt alternatives, and fermented products still fall short of...

Prediction of metabolically healthy obesity based on dietary nutrients: a comparative analysis of six machine learning models with SHAP and LIME interpretation.

PURPOSE: The relationship between dietary nutrient intake and metabolically healthy obesity (MHO) remains poorly understood. This study aimed to const...

Advances in the postoperative care of the liver transplant recipient.

PURPOSE OF REVIEW: Survival rates following liver transplantation now exceed 90% at one year. However, the patient group undergoing liver transplantat...

Predicting Attrition in a Public Nutrition Education Program: A Machine Learning Approach.

OBJECTIVE: To develop a machine learning model to identify adult Expanded Food and Nutrition Education Program (EFNEP) participants at high risk of at...

Development of an explainable machine learning model for predicting depression in adults with type 2 diabetes mellitus: A cross-sectional SHAP-based analysis of NHANES 2009-2023.

Depression (DEP) is a common yet underdiagnosed comorbidity in adults with type 2 diabetes mellitus (T2DM), worsening glycemic control and increasing ...

Multidisciplinary prediction of running-related injuries using machine learning.

The causes of endurance running-related injury (RRI) are multifactorial, yet little research has been conducted which utilizes multidisciplinary risk ...

Assessment of iodine nutrition status in individual adults using machine learning: a cross-sectional study integrating multidimensional features.

Machine learning models for identifying urinary incontinence in women with a history of hysterectomy using basic demographic and clinical characteristics: A cross-sectional study.

BACKGROUND: Urinary incontinence (UI) in women with a history of hysterectomy represents a significant global health concern. It is crucial to clarify...

Wearable electrochemical biosensors for non-invasive sport doping control: sweat and saliva as dual biofluid platforms.

The integrity of competitive athletics is increasingly compromised by sophisticated pharmacologies, rendering traditional sporadic testing of urine an...

Association of urinary heavy metals with osteoporosis in US adults using interpretable machine learning.

BACKGROUND: Exposure to heavy metals in the environment has always been the focus of public concern. More and more evidence suggests that heavy metal ...

Closing the paper mines.

Scientific fakery is a centuries old problem. Twinned with the long history of hard-working scientists earning fame for genuine discoveries, runs a ta...

Association between red cell distribution width-albumin ratio and osteoarthritis in middle-aged and older adults: Analysis of NHANES data (1999-2018).

OBJECTIVE: This study aimed to investigate the association between the Red blood cell distribution width-to-albumin ratio (RAR) and osteoarthritis (OA...

Autoencoders reveal polyunsaturated fatty acids (PUFA)-Related metabolic signature linked to cancer risk.

BACKGROUND: Metabolomics is a valuable tool for characterising biological mechanisms involved in cancer development, but produces complex datasets wit...

Large Language Model-Assisted Research Question Development in Public Health: A Case Study in the Special Supplemental Nutrition Program for Women, Infants, and Children (WIC).

OBJECTIVE: To assess the feasibility of using large language models (LLMs) to develop research questions about changes to the Special Supplemental Nut...

Artificial Intelligence and Ocular Imaging in the Evaluation of Neurologic Disorders: The New Era of Neuro-Oculomics?

Links between the eye and the central nervous system (CNS) have been recognized since the origins of the ophthalmoscope. Owing to the elegant topograp...

Artificial Intelligence in Nutrigenomics: A Critical Review on Functional Food Insights and Personalized Nutrition Pathways.

BACKGROUND: This review critically evaluates the applications of artificial intelligence in nutrigenomics, focusing on its role in interpreting functi...

Development of an individualized prediction model for dynamic adaptations in performance and immune function associated with dietary patterns in endurance athletes using machine learning.

BACKGROUND: Psychological resilience significantly influences immune function and health outcomes in high-stress populations, yet mechanisms underlyin...

Health sciences students' attitudes toward artificial intelligence: predictors of ethical awareness, clinical decision-making, and public health perceptions-a cross-sectional study.

This study investigates health sciences students' attitudes toward artificial intelligence (AI) and the implications for ethical awareness, clinical d...