Latest AI and machine learning research in health policy for healthcare professionals.
The development potential of China's medical insurance market is huge, and the research on medical i...
Electrocoagulation (EC) is a promising alternative for decentralized drinking water treatment in rur...
INTRODUCTION: Remote-access thyroidectomy has been reported in the pediatric population in a limited...
OBJECTIVE: Social robot interventions are being implemented to reduce cognitive decline, depression,...
Cocrystal engineering as an effective way to modify solid-state properties has inspired great intere...
Socially assistive devices such as care robots or companions have been advocated as a promising tool...
Agricultural productivity can be impaired by poor irrigation water quality. Therefore, adequate vuln...
AIM: This study aims to investigate the effects of robot-assisted gait training (RAGT) frequency on ...
BACKGROUND AND AIMS: The quality of esophagogastroduodenoscopy (EGD) can have great impact on the de...
Various vision-threatening eye diseases including age-related macular degeneration (AMD) and central...
BACKGROUND: Laboratory medicine has reached the era where promises of artificial intelligence and ma...
PURPOSE: This study aimed to use deep learning-based dose prediction to assess head and neck (HN) pl...
OBJECTIVE: Robot-assisted gait training (RAGT) is often used as a rehabilitation tool for neurologic...
BACKGROUND: Few, if any estimates of cost-effectiveness for locomotor training strategies following ...
Medical artificial intelligence (AI) has been moving from the research phase to clinical implementat...
OBJECTIVE: The purpose of this study was to use a deep learning model and a traditional statistical ...
OBJECTIVE: To demonstrate similar image quality with deep learning image reconstruction (DLIR) in re...
PURPOSE: To characterize the performance of the Precise Image (PI) deep learning reconstruction (DLR...
China implemented a strict lockdown policy to prevent the spread of COVID-19 in the worst-affected r...
Our aim was to predict future high-cost patients with machine learning using healthcare claims data....
Deep learning methods, which have strong capabilities for mapping highly nonlinear relationships wit...