DataZapp brings AI and machine learning to deliver affordable, predictive demand generation and marketing data for home ...
The efficient management of hospital resources, particularly in terms of bed utilisation and staff allocation, is increasingly critical in modern healthcare systems. Predictive modelling for hospital ...
Researchers, including the University of Tennessee, Knoxville’s Belinda Akpa, are using predictive modeling and machine ...
The Opioid Risk Tool for Opioid Use Disorder may help identify patients with chronic noncancer pain at increased risk for OUD ...
The Southern Maryland Chronicle on MSN
How are QA teams using machine learning to predict test failures in real time?
QA teams now use machine learning to analyze past test data and code changes to predict which tests will fail before they run. The technology examines patterns from previous test runs, code commits, ...
Cardiovascular disease continues to be the leading cause of death worldwide. To save lives, constantly improving diagnostic ...
The researchers suggest that this improvement in diagnostic performance for OFC biomarker discovery can be used to develop a diagnostic alternative for food allergy that is scalable and more efficient ...
In an interview with Technology Networks, Dr. Daniel Reker discusses how machine learning is improving data-scarce areas of drug discovery.
PLSKB: An Interactive Knowledge Base to Support Diagnosis, Treatment, and Screening of Lynch Syndrome on the Basis of Precision Oncology We used an innovative machine learning approach to analyze ...
Keysight Technologies has introduced a new Machine Learning Toolkit as part of its latest Device Modelling Software Suite, aiming to reduce the time required for semiconductor device modelling and ...
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