Latest AI and machine learning research in parenting for healthcare professionals.
Introduction: Accurate stratification of hard atherosclerotic cardiovascular disease (ASCVD) risk remains challenging despite advances in prevention. Liver function biomarkers (LFBs), particularly gamma - glutamyl transferase (GGT), have been linked to cardiovascular outcomes, yet their contribution to hard ASCVD risk prediction is not well defined. Methods: This study analyzed data from the Natio...
The transition of genomics to a predictive intelligence discipline is driven by the advent of genomic foundation models. While substantial progress has been observed in human-centric models, plant genomics, particularly for the staple crops, remains hindered by a lack of models. Here we introduce OneGenomeRice (OGR), a genomic foundation model for rice (Oryza sativa) engineered by a Mixture of Exp...
Mutation-induced drug resistance is a major contributor to the failure of targeted cancer therapies, particularly in tumors driven by mutations in the...
Accurate estimation of food nutrition plays a vital role in promoting healthy dietary habits and personalized diet management. Most existing food data...
Machine learning models trained on observational data from one environment frequently fail when deployed in another, because standard learning algorit...
Parametric Computer-Aided Design (CAD) of articulated assemblies is essential for product development, yet generating these multi-part, movable models...
Nutrition estimation of meals from visual data is an important problem for dietary monitoring and computational health, but existing approaches largel...
Parametric Computer-Aided Design (CAD) of articulated assemblies is essential for product development, yet generating these multi-part, movable models...
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 ...
Humanoid robot technologies have demonstrated immense potential for minimally invasive surgery (MIS). Unlike dedicated multi-arm surgical platforms, t...
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...
Managing diabetes-related conditions is time-intensive and cognitively demanding for patients and caregivers, requiring ongoing glucose monitoring, di...
Background: Conventional clinical indicators of periodontitis progression detect disease after irreversible tissue destruction has occurred. Molecular...
Phytolith analysis is a crucial tool for reconstructing past vegetation and human activities, but traditional methods are severely limited by labour-i...
Unified multimodal models target joint understanding, reasoning, and generation, but current image editing benchmarks are largely confined to natural ...
Model Medicine is the science of understanding, diagnosing, treating, and preventing disorders in AI models, grounded in the principle that AI models ...
Realistic shadow generation is crucial for achieving seamless image compositing, yet existing methods primarily focus on single-object insertion and o...
Realistic shadow generation is crucial for achieving seamless image compositing, yet existing methods primarily focus on single-object insertion and o...