Latest AI and machine learning research in us health policy for healthcare professionals.
The reliability of machine learning models can be compromised when trained on low quality data. Many...
Social species rely on the ability to modulate feedback-monitoring in social contexts to adjust one'...
Health system data incompletely capture the social risk factors for drug overdose. This study aimed ...
We assessed the generalizability of deep learning models and how to improve it. Our exemplary use-ca...
BACKGROUND: Robotic prostatectomy is a costly new technology, but the costs may be offset by changes...
Precise characterization and analysis of anterior chamber angle (ACA) are of great importance in fac...
This study aimed to evaluate the effect of an artificial intelligence (AI) support system on breast ...
The paper is concerned with the consensus problem in a multi-agent system such that each agent has b...
Adult-onset Still's disease (AOSD) is an autoinflammatory disease with multisystem involvement. Earl...
PURPOSE: Consensus molecular subtyping (CMS) of colorectal cancer has potential to reshape the color...
The optimization of ecological water supplement scheme in Momoge National Nature Reserve (MNNR), usi...
Real-world evidence (RWE), conclusions derived from analysis of patients not treated in clinical tri...
Surgeons and residents report using videos to prepare for procedures, with a preference for open ac...
BACKGROUND: Twitter is a potentially valuable tool for public health officials and state Medicaid pr...
Artificial intelligence (AI) presents a key opportunity for radiologists to improve quality of care ...
OBJECTIVE: To develop and validate a machine-learning algorithm to improve prediction of incident OU...
BACKGROUND: We tested the added value of 3D-vision on procedure time and surgical performance during...
As the dominant component for precise motion measurement, angle sensors play a vital role in robotic...
The biological complexity reflected in histology images requires advanced approaches for unbiased pr...
To analyze predictors of open conversion during minimally invasive partial nephrectomy (MIPN) for c...
We propose a machine learning driven approach to derive insights from observational healthcare data ...