AI may be more accurate vs. traditional methods at classifying patients into prostate cancer risk groups

Share on facebook
Share on twitter
Share on linkedin
Share on email
Share on print

For localized prostate cancer, multimodal artificial intelligence models have revealed a more accurate way to assess prostate cancer risk.  By combining advanced artificial intelligence with digital pathology images and clinical data, researchers developed a way to approach risk classification that outperforms traditional methods. These findings were published in JCO Precision Oncology. The research found that...

To access this subscriber-only content please log in or subscribe.

If your institution has a site license, log in with IP-login or register for a sponsored account.*
*Not all site licenses are enrolled in sponsored accounts.

Login Subscribe
Table of Contents

YOU MAY BE INTERESTED IN

Pfizer Inc. and Astellas Pharma Inc. announced positive topline results from the overall survival analysis from the phase III EMBARK study evaluating Xtandi (enzalutamide), an androgen receptor signaling inhibitor, in combination with leuprolide, and as a monotherapy in men with non-metastatic hormone-sensitive prostate cancer with biochemical recurrence at high risk for metastasis.
Patients affected by cancer are increasingly turning to artificial intelligence-powered chatbots, such as ChatGPT and Gemini, for answers to pressing health questions. These tools, available around the clock and free from geographic or scheduling constraints, are appealing when access to medical professionals is limited by financial, language, logistical, or emotional barriers. 

Never miss an issue!

Get alerts for our award-winning coverage in your inbox.

Login