Utilizing artificial intelligence along with traditional pathology offers promise for swiftly developing treatment plans for patients with non-small cell lung cancers, a team led by UT Southwestern Medical Center researchers discovered.
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...
An international, multidisciplinary team of leading neuro-oncology researchers and clinicians has released new recommendations for good clinical practice—a set of guidelines that helps ensure clinical trial results are reliable, and patients are protected—regarding the use of artificial intelligence methods to more accurately diagnose, monitor, and treat brain cancer patients. The team recently published two companion...
