Latest AI and machine learning research in health policy for healthcare professionals.
Navigation and manipulation in open-world environments remain unsolved challenges in the Embodied AI. The high cost of commercial mobile manipulation robots significantly limits research in real-world scenes. To address this issue, we propose AhaRobot, a low-cost and fully open-source dual-arm mobile manipulation robot system with a hardware cost of only $1,000 (excluding optional computational ...
Perinatal complications, defined as conditions that arise during pregnancy, childbirth, and the immediate postpartum period, represent a significant burden on maternal and neonatal health worldwide. Factors contributing to these disparities include limited access to quality healthcare, socioeconomic inequalities, and variations in healthcare infrastructure. Addressing these issues is crucial for...
This paper investigates the critical issue of data poisoning attacks on AI models, a growing concern in the ever-evolving landscape of artificial in...
Blind Face Restoration (BFR) addresses the challenge of reconstructing degraded low-quality (LQ) facial images into high-quality (HQ) outputs. Conve...
Image quality scoring and interpreting are two fundamental components of Image Quality Assessment (IQA). The former quantifies image quality, while ...
As recent text-conditioned diffusion models have enabled the generation of high-quality images, concerns over their potential misuse have also grown...
Ultra-high quality artistic style transfer refers to repainting an ultra-high quality content image using the style information learned from the sty...
The rapid advancement of Large Language Models (LLMs) has increased the complexity and cost of fine-tuning, leading to the adoption of API-based fin...
Recent inductive logic programming (ILP) approaches learn optimal hypotheses. An optimal hypothesis minimises a given cost function on the training ...
Older people are susceptible to fall due to instability in posture and deteriorating health. Immediate access to medical support can greatly reduce ...
Femoral artery access is essential for numerous clinical procedures, including diagnostic angiography, therapeutic catheterization, and emergency in...
Access to real-world healthcare data is limited by stringent privacy regulations and data imbalances, hindering advancements in research and clinica...
Reinforcement learning agents are fundamentally limited by the quality of the reward functions they learn from, yet reward design is often overlooke...
Large Action Models (LAMs) have revolutionized intelligent automation, but their application in healthcare faces challenges due to privacy concerns,...
In the face of intensified datafication and automation in public sector industries, frameworks like design justice and the feminist practice of refu...
Digitalization in the construction industry has become essential, enabling centralized, easy access to all relevant information of a building. Autom...
Dementia, a neurological disorder impacting millions globally, presents significant challenges in diagnosis and patient care. With the rise of priva...
In this paper, we explore a novel image matting task aimed at achieving efficient inference under various computational cost constraints, specifical...
The integration of artificial intelligence (AI) into surgery raises significant ethical concerns, including the impact on autonomy, human authority an...
Image quality plays an important role in the performance of deep neural networks (DNNs) and DNNs have been widely shown to exhibit sensitivity to ch...