Latest AI and machine learning research in prevention for healthcare professionals.
Pre-trained vision encoders like DINOv2 have demonstrated exceptional performance on unimodal tasks. However, we observe that their feature representations are poorly aligned across different modalities. For instance, the feature embedding for an RGB image and its corresponding depth map of the same scene exhibit a cosine similarity that is nearly identical to that of two random, unrelated images....
Objective: Electronic Health Record (EHR)-based trial emulation can support translation of randomized clinical trial (RCT) evidence into practice, yet emulations often diverge from published RCT results. We hypothesized that these discrepancies are structured and learnable properties of a health system's data-generating process, and that autonomous agentic workflows can generate discrepancies at t...
Identifying physiological sweet spots (optimal ranges for homeostasis) is essential for precision medicine. However, traditional statistical methods o...
How habitual diet influences the gut microbiome and plasma metabolome across insulin resistance states remains unclear. We conducted year-long multi-o...
Background: Risk screening for pre-eclampsia relies on accurate gestational age assessment, but routine access to ultrasound-based gestational dating ...
Ductular Reactions (DRs) are dynamic and complex multicellular responses that occur as a result of various hepatic injuries. Precise identification an...
Background: Conventional evaluations of digital health interventions typically assess mean treatment effects, potentially masking heterogeneous impact...
Background: Artificial intelligence applications for preventive stress monitoring remain limited by dependence on expensive continuous biosensors. We ...
Perivascular adipose tissue (PVAT), an intriguing layer of fat surrounding blood vessels, regulates vascular tone and mediates vascular dysfunction th...
Background: Cardiovascular diseases (CVDs) remain the leading global cause of morbidity and mortality. In clinical practice, 10-year risk prediction t...
Determining physiological stress at high resolution is crucial across diverse settings to enable informed decision-making in the context of health and...
Background: Heart failure with preserved ejection fraction (HFpEF) remains a major therapeutic challenge due to its complex pathophysiology and pronou...
Genome-wide association studies of physical activity traits have mapped numerous loci, yet the molecular mechanisms through which exercise influences ...
Low back pain (LBP) is a pervasive global health challenge, affecting approximately 80% of adults and frequently progressing into chronic or recurrent...
Background Patients with repaired tetralogy of Fallot (rTOF) require lifelong surveillance with cardiovascular magnetic resonance (CMR) and cardiopulm...
Background/ObjectivesHead and neck cancer (HNC) represents the seventh most common cancer diagnosis globally, yet current treatments, including surger...
Causal discovery aims to recover ``what causes what'', but classical constraint-based methods (e.g., PC, FCI) suffer from error propagation, and recen...
Autism spectrum disorder (ASD) is characterized by deficits in social communication and repetitive behaviors/restricted interests that may be diagnose...
This paper introduces the Ambient Intelligence Rehabilitation Support (AIRS) framework, an advanced artificial intelligence-based solution tailored ...
Despite years of research and the dramatic scaling of artificial intelligence (AI) systems, a striking misalignment between artificial and human vis...