A new machine-learning-based approach to mapping real-time tumor metabolism in brain cancer patients, developed at the ...

A new machine-learning-based approach to mapping real-time tumor metabolism in brain cancer patients, developed at the ...

A predictive model identifies RA patients at risk of D2T-RA, using machine learning and real-world data for early intervention. Patient-reported outcomes, such as pain and fatigue, are stronger ...

Integration of Telemedicine Consultation Into a Tertiary Radiation Oncology Department: Predictors of Use, Treatment Yield, and Effects on Patient Population Using the scoping review methodology ...

The application of artificial intelligence (AI) for healthcare is transforming patient treatment, from advanced analytics to computerized automated diagnosis. However, with the increased application ...

The second key factor is radical personalisation. Moving beyond basic patient segmentation, true personalisation means ...

Health systems have a large amount of patient data through EHRs and other digital platforms managing administrative tasks and clinical care. The de-identified patient data is useful for creating large ...