Latest AI and machine learning research in health policy for healthcare professionals.
We introduce Biomed-Enriched, a biomedical text dataset constructed from PubMed via a two-stage an...
Diffusion Policy (DP) enables robots to learn complex behaviors by imitating expert demonstrations...
Diffusion models are well known for their ability to generate a high-fidelity image for an input p...
Rapid and reliable vascular access is critical in trauma and critical care. Central vascular cathe...
In the field of image fusion, promising progress has been made by modeling data from different mod...
The quality of the video dataset (image quality, resolution, and fine-grained caption) greatly inf...
Digital health interventions offer promise for scalable and accessible health care, but access is st...
The integration of artificial intelligence (AI) into point-of-care testing (POCT) represents a trans...
Neural networks excel as function approximators, but their complexity often obscures the nature of...
Effective human-AI decision-making balances three key factors: the \textit{correctness} of predict...
Effective human-AI decision-making balances three key factors: the \textit{correctness} of predict...
We present SLICK, a novel framework for precise and robust car damage segmentation that leverages ...
Visual servoing technology has been well developed and applied in many automated manufacturing tas...
Machine Unlearning (MU) aims to update Machine Learning (ML) models following requests to remove t...
Digital terrorism is a major cause of securing patient/healthcare providers data and information. ...
A heterogeneous micro aerial vehicles (MAV) swarm consists of resource-intensive but expensive adv...
The development lifecycle of generative AI systems requires continual evaluation, data acquisition...
Air pollution has emerged as a major public health challenge in megacities. Numerical simulations ...
This paper addresses the scarcity of low-cost but high-dexterity platforms for collecting real-wor...
Traditional decision-based black-box adversarial attacks on image classifiers aim to generate adve...
Most post-disaster damage classifiers succeed only when destructive forces leave clear spectral or...