Prediction of cancer recurrence based on Gleason score alone had 77.9% accuracy, ... 764 machine learning models trained using data from the UPMC cohort were applied to the Stanford/Wisconsin ...

An analysis on 1,194 patients with NSCLC was performed to evaluate the prognostic signatures of quantitative imaging features, extracted with deep learning. 27 In our work, we trained machine learning ...

Findings from the new study—published today in Scientific Reports through an article titled “Objective risk stratification of prostate cancer using machine learning and radiomics applied to ...

A Michigan Tech-developed machine learning model uses probability to more accurately classify breast cancer shown in histopathology images and evaluate the uncertainty of its predictions. Breast ...