Latest AI and machine learning research in obesity for healthcare professionals.
Computer vision models that estimate body mass index (BMI) from facial features offer a non-invasive, low-cost alternative to physical measurement, with uses in telemedicine, emergency care where a scale or measuring tools arent available, automated self-monitoring, and large-scale epidemiological research. Most of these models, however, are trained on government records, social media images, and ...
University students experience disproportionately high rates of common mental health conditions, such as depression, which can impair learning, social functioning, and overall well-being. Although lifestyle interventions such as mindfulness and physical activity can reduce the symptoms, many do not achieve symptomatic remission. Developing new approaches to identify students with poor outcomes cou...
Geospatial foundation models such as the AlphaEarth Foundation produce compact and globally consistent representations of the Earth's surface that tra...
Abstract The gayal (Bos frontalis) is an endangered semi-domesticated bovine species renowned for its high-quality beef. However, its semi-feral lifes...
In this work, we propose a structural variant of the Factorial Hidden Markov Model (FHMM) for the analysis of disease trajectories in patients with Ty...
Background Glucagon-like peptide-1 (GLP-1) receptor agonists and sodium-glucose cotransporter-2 (SGLT2) inhibitors are increasingly used for type 2 di...
Background. Phthalates are hypothesised to act as metabolic disruptors, and machine learning applied to the National Health and Nutrition Examination ...
Existing general-purpose biomedical knowledge graphs tend to focus on disease mechanisms and drug repurposing, leaving multiomic and wellness-relevant...
Background: Low birth weight remains a primary driver of neonatal and infant mortality in Ethiopia. Machine learning models can assist early risk iden...
Background: The growing burden of lifestyle-related chronic diseases has increased the need for clinically interpretable decision-support tools capabl...
Importance Socioeconomic disadvantage is associated with accelerated brain aging. However, the modifiable factors accounting for this association, and...
Abstract Background The gut microbiome has been widely studied in the context of obesity, and yet the reported associations vary widely across populat...
Plaque assays remain the gold standard for bacteriophage quantification, but routine plaque counting is labor-intensive, time-consuming, and poorly su...
BACKGROUND: Liberation from invasive mechanical ventilation (IMV) is a central therapeutic objective in acute respiratory failure (ARF). While lung-pr...
As populations age, cognitive decline from mild cognitive impairment (MCI) to dementia is a defining health challenge of the coming decades, yet routi...
Conventional subgroup analyses can yield unstable and difficult-to-interpret conclusions, especially in observational biomedical data where each indiv...
Background: Excess epicardial adipose tissue (EAT) is associated with cardiovascular-kidney-metabolic (CKM) dysfunction, but its assessment has tradit...
Objective. To develop an interpretable multimodal machine-learning model for risk stratification of the rapid pain progression phenotype in knee osteo...
Background: Prior studies on metabolite associations with incident heart failure (HF) used billing code-based definitions and lacked the data on left ...
Background: University students experience substantial psychological well-being and body-image concerns, while scalable, personalized digital support ...