Latest AI and machine learning research in diet & nutrition for healthcare professionals.
Accurate estimation of food nutrition plays a vital role in promoting healthy dietary habits and personalized diet management. Most existing food datasets primarily focus on Western cuisines and lack sufficient coverage of Chinese dishes, which restricts accurate nutritional estimation for Chinese meals. Moreover, many state-of-the-art nutrition prediction methods rely on depth sensors, restrictin...
Machine learning models trained on observational data from one environment frequently fail when deployed in another, because standard learning algorithms exploit spurious correlations alongside causal ones. Invariant learning methods address this problem by seeking representations that support stable prediction across training environments, but their behavior on tabular data remains poorly charact...
Nutrition estimation of meals from visual data is an important problem for dietary monitoring and computational health, but existing approaches largel...
Cyclic peptides are recognized as versatile scaffolds for therapeutic and functional applications due to their structural stability and resistance to ...
Recent advancements in Vision-Language Models (VLMs) have revolutionized general visual understanding. However, their application in the food domain r...
Accurate dietary assessment is critical for precision nutrition, yet most image-based methods rely on a single pre-consumption image and provide only ...
The rapid advancement of AI research automation systems--including AI Scientist, data-to-paper, and Agent Laboratory--has demonstrated the potential f...
Background: The 2017 American College of Cardiology/American Heart Association (ACC/AHA) guideline lowered diagnostic threshold for hypertension, enco...
Background High body mass index (BMI) presents a serious and ongoing global health challenge. However, the difficulty of high BMI intervention has not...
Objective: To develop and validate a multivariable prediction model and clinically actionable risk score for vaginal birth after cesarean (VBAC) succe...
Frailty is a prevalent geriatric syndrome, and the shortage of objective biomarkers restricts its early diagnosis and intervention. This study aimed t...
Managing diabetes-related conditions is time-intensive and cognitively demanding for patients and caregivers, requiring ongoing glucose monitoring, di...
Objectives Patients with osteoarthritis (OA) affecting multiple joints have poorer health outcomes than those without, yet most research examines isol...
Osteoporosis is a skeletal disease typically diagnosed using dual-energy X-ray absorptiometry (DXA), which quantifies areal bone mineral density but o...
Osteoporosis is a skeletal disease typically diagnosed using dual-energy X-ray absorptiometry (DXA), which quantifies areal bone mineral density but o...
Purpose Medical imaging typically generates 12- to 16-bit formats, yet conversion to 8-bit is often required. While deep learning has been widely expl...
Caption quality has emerged as a critical bottleneck in training high-quality text-to-image (T2I) and text-to-video (T2V) generative models. While vis...
Diet plays a critical role in human health, with growing evidence linking dietary habits to disease outcomes. However, extracting structured dietary k...
Background: Cardiovascular disease remains the leading cause of global morbidity and mortality. The original My Heart Counts smartphone application de...
Lifestyle and environmental factors such as diet, physical activity, residential greenspace exposure, alcohol consumption, and sleep are increasingly ...