Flexynesis uses deep learning to evaluate multi-omics data as well as specially processed texts and images, including CT or ...
Nearly 50 new cancer therapies are approved every year. This is good news. "But for patients and their treating physicians, ...
The deep-learning model used the whole “breast architecture,” not just calcification, to predict MACE risk in middle-aged ...
Deep learning can both strengthen the building blocks of future networks and uncover hidden risks in widely used applications ...
In the rapidly advancing field of computational biology, a newly peer-reviewed review explores the transformative role of deep learning techniques in revolutionizing protein structure prediction. The ...
Background Cardiovascular risk is underassessed in women. Many women undergo screening mammography in midlife when the risk ...
A research team led by Oak Ridge National Laboratory has developed a new method to uncover the atomic origins of unusual ...
Scientists have developed and tested a deep-learning model that could support clinicians by providing accurate results and ...
Traditional machine learning methods like Support Vector Machines, Random Forest, and gradient boosting have shown strong performance in classifying device behaviors and detecting botnet activity.
A new study introduces an innovative method to monitor sludge moisture content in real-time, combining jet imaging and deep learning to transform wastewater treatment processes.
Some results have been hidden because they may be inaccessible to you
Show inaccessible results
Feedback