AI DICOM standardisation was associated with faster radiology reading times and accurate metadata labelling. Learn more about ...

Developing the POTOMAC Model: A Novel Prediction Model to Study the Impact of Lymphopenia Kinetics on Survival Outcomes in Head and Neck Cancer Via an Ensemble Tree-Based Machine Learning Approach The ...

Assessment of quality and safety indicators (QSIs) remains often based on time-consuming manual Electronic Health Record (EHR) review. As part of a pilot study to examine the feasibility of automating ...

Public imaging datasets are critical for the development and evaluation of automated tools in cancer imaging. Unfortunately, many do not include annotations or image-derived features, complicating ...