Latest AI and machine learning research in diet & nutrition for healthcare professionals.
The aim of this paper is to (1) identify textual and visual themes and sub-themes associated with the #wellbeing hashtag on Instagram, (2) assess their varying levels of engagement and (3) investigate gender bias present in the analysed visual narratives. This study employs a range of big data analysis techniques to investigate various dimensions of wellbeing on Instagram. Initially, a sample of 9...
Image based dietary assessment offers a scalable alternative to self reported food diaries, yet fine-grained food recognition remains challenging due to high intra-class variability and visually similar dishes. This study presents OliveGemma, a vision language model for recognising and reasoning about Mediterranean and European cuisine. Built on the open-weight PaliGemma-2-3B architecture, OliveGe...
Background: Dietary assessment is the cornerstone of clinical management and research studies evaluating diet and health. Traditional methods such as ...
Conventional subgroup analyses can yield unstable and difficult-to-interpret conclusions, especially in observational biomedical data where each indiv...
Food image segmentation plays a vital role in health-related applications such as nutrition tracking and personalized health monitoring. However, exis...
Background: Prior studies on metabolite associations with incident heart failure (HF) used billing code-based definitions and lacked the data on left ...
Abstract Background Despite a rising global psychiatric burden, a treatment gap persists where the majority of symptomatic individuals remain unmedica...
Multimodal Large Language Models (MLLMs) are increasingly used for dietary assessment from meal images, where retrieval-augmented grounding was shown ...
Purpose The application of machine learning (ML) to osteoporosis prediction has expanded rapidly, yet no comprehensive meta-analysis has synthesized t...
Background and objectives: In recent years, the need to develop analytical strategies for healthy aging has assumed great importance. In this study, w...
Background Hypercapnia may indicate a primary ventilatory syndrome, a complication of another illness, or an epiphenomenon of severe disease. The pres...
Background: Iron Deficiency Anemia (IDA) is one of the most prevalent nutritional disorders globally and a leading cause of Disability Adjusted Life Y...
Endometrial cancer (EC) incidence is closely linked to metabolic and hormonal factors. The TyGFI, a composite indicator integrating the triglyceride-g...
The clinical utility of monitoring longitudinal changes in musculoskeletal trajectories, including bone mineral density (BMD), muscle strength, height...
Background: Dopamine (DA) is a neurotransmitter critically involved in food-related reinforcement learning. While mesolimbic DA reward-associated sign...
Generative AI tools such as ChatGPT are increasingly used by the public to seek guidance on diet and physical activity for type 2 diabetes (T2D) preve...
Background: Large language models (LLMs) offer promise for systematic review data extraction, but performance in complex multidisciplinary domains and...
Diagnosed diabetes affects approximately 38.4 million Americans, but its burden is not evenly distributed across U.S. counties. Existing machine-learn...
Background Hypertension remains one of the most challenging healthcare problems in the community. It is a common, measurable, and treatable condition ...
Food images often contain several visible ingredients, so assigning one dish label to an entire image hides important visual structure. This work stud...