Initially, evaluation of the predictive performance of machine-learned algorithms involves ... development and represent the majority of published reports describing machine learning in medicine.3 ...

Identifying the problem of DDoS attacks is a major problem in machine learning. To achieve this ... This cycle requirement is data collection planning, implementation, and evaluation. Results are ...

A research team led by Prof. Wan Yinhua from the Institute of Process Engineering (IPE) of the Chinese Academy of Sciences ...

As the use of machine learning algorithms in health care continues ... for Medicare and Medicaid Services (CMS) for quality performance assessments, 12 are common among health insurers.

The used machine-learning techniques to determine which health and lifestyle factors best predict cognitive performance across the adult lifespan.

A new study offers insight into the health and lifestyle indicators—including diet, physical activity and weight—that align ...

signaling potential degradation in performance. By capturing production inferencing signals and leveraging continuous evaluation, Azure ML enables organizations to maintain and optimize their machine ...

Researchers at the Department of Energy's Lawrence Berkeley National Laboratory (Berkeley Lab) have made a breakthrough in ...