Latest AI and machine learning research in parenting for healthcare professionals.
In the US, pre-diabetes and diabetes are increasing in prevalence alongside other chronic diseases. Hemoglobin A1c is the most common diagnostic test for diabetes performed in the US, but it has known inaccuracies in the setting of other chronic diseases. To determine if easily obtained clinical data could be used to improve the diagnosis of pre-diabetes and diabetes compared to hemoglobin A1c alo...
Anemia significantly impacts adolescent girls’ health and quality of life in Ethiopia. Effective interventions require identifying key risk factors and predicting anemia severity. While traditional studies primarily use statistical methods, this research aims to leverage machine learning models to predict anemia risk and analyze contributing socio-economic, environmental, and cultural factors. We ...
This study explores the use of advanced Natural Language Processing (NLP) techniques to enhance food classification and dietary analysis using raw tex...
Quantifying human health and disease necessitates a transformative framework capable of integrating diverse biomedical data in a standardized manner. ...
Inflammatory bowel disease (IBD) research is a dynamic field. However, the growing volume of electronic health records (EHRs) and research data presen...
According to an ADA report, approximately 15% of the US population requires dental care annually but does not receive it. Access to dental care, parti...
Many adults in high-income countries carry a device capable of measuring physical- activity behaviour. Thus, there is public health need to understand...
Malnutrition significantly impacts surgical outcomes yet is difficult to identify preoperatively. Few studies have investigated the association betwee...
Maternal mental health (MMH) disorders, particularly depression and anxiety, are major public health concerns in low- and middle-income countries (LMI...
The use of machine learning (ML) methods in medical prognostic modelling is gaining popularity, yet all currently available source models were designe...
Understanding who benefits most from investments in water, sanitation, and hygiene (WaSH) interventions can elucidate causal pathways, uncover complex...
Cancer is increasingly recognized as a metabolic disease with strong nutritional determinants. Recent advances in multi-omics technologies and artific...
Machine learning (ML) models are widely used to predict body mass index (BMI), yet their fairness across socioeconomic and caste groups remains uncert...
Synthetic data can be the solution to privacy requirements, can enrich datasets limited by underrepresentation of certain subgroups/minorities, combat...
Amyotrophic lateral sclerosis (ALS) is a fatal neurodegenerative disorder with a largely unknown duration and pathophysiology of the pre-diagnostic ph...
Access to high-quality data provides the foundation for biomedical research. But data access is often limited or challenging due to privacy constraint...
The potential of artificial intelligence (AI) to personalize dietary and exercise advice for obesity management is increasingly evident. However, the ...
Cardiovascular disease (CVD) remains the foremost contributor to global illness and death, underscoring the critical need for effective tools that can...
Sleep, physical activity, and nutrition (SPAN) are major modifiable risk factors for cardiovascular disease, yet the minimum and optimal combined impr...
Current Czech national food-based dietary guidelines are outdated and do not reflect the most recent scientific evidence, nor considerations of sustai...