Latest AI and machine learning research in health policy for healthcare professionals.
Policy optimization in high-dimensional continuous control for robotics remains a challenging proble...
RLVR and OPD have become standard paradigms for post-training. We provide a unified analysis of thes...
Face Recognition (FR) is used in a variety of application domains, from entertainment and banking to...
Patient portals now give individuals direct access to their electronic health records (EHRs), yet ac...
Touchless interaction with medical images is becoming increasingly important in the surgical field, ...
Cardiotoxicity remains a major cause of drug attrition and post-market withdrawal, yet the vast majo...
Background: Mechanical ventricular unloading and systemic circulatory support with left ventricular ...
Low-cost FPGA platforms can broaden access to neuromorphic systems research, but current spiking neu...
Background: Chronic conditions such as hypertension can significantly disrupt daily life and emotion...
Background Depressive symptoms among reproductive-aged women represent a major public health concern...
Geographic context is often consider relevant to motor insurance risk, yet public actuarial datasets...
Daily infrastructure management in preparation for disasters is critical for urban resilience. When ...
Clinical research involves labor-intensive processes such as study design, cohort construction, mode...
The effectiveness of Direct Preference Optimization (DPO) depends on preference data that reflect th...
This study evaluates the feasibility of implementing artificial intelligence (AI)-driven disease sur...
ObjectivesTo develop and evaluate predictive models for unused outpatient appointments (missed or ca...
Clinical decision-making often involves selecting tests that are costly, invasive, or time-consuming...
Remote sensing understanding inherently requires multi-resolution observation, since different targe...
Classifier-free Guidance (CFG) lets practitioners trade-off fidelity against diversity in Diffusion ...
Extending LLM context windows is hindered by scarce high-quality long-context data. Recent methods s...
Multimodal reasoning models (MRMs) trained with reinforcement learning with verifiable rewards (RLVR...