Latest AI and machine learning research in health policy for healthcare professionals.
Disaster robotics is a growing field that is concerned with the design and development of robots for disaster response and disaster recovery. These robots assist first responders by performing tasks that are impractical or impossible for humans. Unfortunately, current disaster robots usually lack the maneuverability to efficiently traverse these areas, which often necessitate extreme navigational ...
Robotic intravenous poles are automated supportive instrument that needs to be triggered by patients to hold medications and needed supplies. Healthcare engineering of robotic intravenous poles is advancing in order to improve the quality of health services to patients worldwide. Existing intravenous poles in the market were supportive to patients, yet they constrained their movement, consumed the...
Hearing loss is the leading human sensory system loss, and one of the leading causes for years lived with disability with significant effects on quali...
Given the powerful implications of relationship quality for health and well-being, a central mission of relationship science is explaining why some ro...
The past decade in rheumatology has seen tremendous innovation in digital health technologies, including the electronic health record, virtual visits,...
OBJECTIVE: Complex phenotypes captured on histological slides represent the biological processes at play in individual cancers, but the link to underl...
BACKGROUND: Chronic spinal pain conditions affect millions of US adults and carry a high healthcare cost burden, both direct and indirect. Conservativ...
This article presents a mapping review of the literature concerning the ethics of artificial intelligence (AI) in health care. The goal of this review...
Telemedicine is the provision of healthcare-related services from a distance and is poised to move healthcare from the physician's office back into th...
Artificial intelligence (AI) is seen as a strategic lever to improve access, quality, and efficiency of care and services and to build learning and va...
Although deep learning exhibits advantages in various applications involving multimodal data, it cannot effectively solve the class-imbalance problem....
Classifiers that can be implemented on chip with minimal computational and memory resources are essential for edge computing in emerging applications ...
To analyze predictors of open conversion during minimally invasive partial nephrectomy (MIPN) for cT1 renal masses. The National Cancer Database (NC...
Electroencephalography (EEG) datasets are often small and high dimensional, owing to cumbersome recording processes. In these conditions, powerful mac...
Starting renal replacement therapy (RRT) for patients with chronic kidney disease (CKD) at an optimal time, either with hemodialysis or kidney transpl...
For the agricultural food production sector, the control and assessment of food quality is an essential issue, which has a direct impact on both human...
BACKGROUND: Robot-assisted laparoscopic pyeloplasty (RALP) is a commonly performed procedure in children, but its actual cost implications on the heal...
Detecting and analyzing patient insights from social media enables healthcare givers to better understand what patients want and also to identify thei...
Oral cancer is easily detectable by physical (self) examination. However, many cases of oral cancer are detected late, which causes unnecessary morbid...
Patient-specific induced pluripotent stem cell-derived cardiomyocytes (iPSC-CMs) offer an attractive experimental platform to investigate cardiac dise...