Latest AI and machine learning research in health policy for healthcare professionals.
We propose a new framework for multi-agent reinforcement learning (MARL), where the agents cooperate in a time-evolving network with latent community structures and mixed memberships. Unlike traditional neighbor-based or fixed interaction graphs, our community-based framework captures flexible and abstract coordination patterns by allowing each agent to belong to multiple overlapping communities...
BACKGROUND: To improve healthcare quality and empower patients, federal legislation requires nationwide interoperability of electronic health records (EHRs) through Fast Healthcare Interoperability Resources (FHIR) application programming interfaces. Nevertheless, key barriers to patient EHR access-limited functionality, English, and health literacy-persist, impeding equitable access to these bene...
: The healthcare sector is under increasing pressure due to an ageing population, rising multimorbidity, and a projected global workforce shortage of ...
Artificial intelligence (AI) and assistive robotics can transform older-person care by offering new, personalised solutions for an ageing population. ...
Artificial intelligence (AI) has transformed healthcare, particularly in robot-assisted surgery, rehabilitation, medical imaging and diagnostics, virt...
Predictive manipulation has recently gained considerable attention in the Embodied AI community due to its potential to improve robot policy perform...
Learning navigation in dynamic open-world environments is an important yet challenging skill for robots. Most previous methods rely on precise local...
Large language models achieve high task performance yet often hallucinate or rely on outdated knowledge. Retrieval-augmented generation (RAG) addres...
This article examines the expanding role of Artificial Intelligence (AI) in healthcare and associated human rights concerns, including whether new EU ...
Health literacy is essential for promoting well-being and the ability to make informed decisions. We investigated the level of health literacy in Braz...
Current methods for producing cardiomyocytes from human induced pluripotent stem cells (hiPSCs) using 2D monolayer differentiation are often hampered ...
Artificial intelligence (AI) has shown effectiveness in various industries, particularly within healthcare sectors. In Nepal, there are limited insigh...
Since the early 1970s, technology has increasingly become integrated into the healthcare field. Today, artificial intelligence (AI) and machine learni...
Recent breakthroughs in generative models-particularly diffusion models and rectified flows-have revolutionized visual content creation, yet alignin...
Traditional topic models often struggle with contextual nuances and fail to adequately handle polysemy and rare words. This limitation typically res...
Protecting power transmission lines from potential hazards involves critical tasks, one of which is the accurate measurement of distances between po...
Next Best View (NBV) algorithms aim to acquire an optimal set of images using minimal resources, time, or number of captures to enable efficient 3D ...
Magnetic Resonance Imaging (MRI) is critical for clinical diagnostics but is often limited by long acquisition times and low signal-to-noise ratios,...
Purpose: Deep learning has demonstrated strong potential for MRI reconstruction, but conventional supervised learning methods require high-quality r...