Doctors have developed an artificial intelligence tool that can predict which men with prostate cancer will benefit from a drug that halves the risk of dying. Abiraterone has been described as a "gamechanger" treatment for the disease, which is the most common form of cancer in men in more than 100 countries. It has already helped hundreds of thousands with advanced prostate cancer to live longer. But some countries, including England, have stopped short of offering the "spectacular" drug more widely to men whose disease has not spread. Now a team from the US, UK and Switzerland have built an AI test that shows which men would most likely benefit from abiraterone. The "exciting" breakthrough will enable healthcare systems to roll out the drug to more men, and spare others unnecessary treatment.

Doctors believe Artificial Intelligence is now saving lives, after a major advancement in breast cancer screenings. A.I. is detecting early signs of the disease, in some cases years before doctors would find the cancer on a traditional scan. Department of Veterans Affairs researchers at five medical centers are working together to develop an artificial intelligence algorithm that can predict aggressive prostate cancer. The new research study began July 1, expanding to 14 sites. It will analyze data from more than 5,000 veterans who were diagnosed with high-risk prostate cancer and have undergone initial treatment.

Prostate cancer can be low- or high-risk to the patient's health. Current screening on the basis of prostate-specific antigen (PSA) levels has a tendency towards both false positives and false negatives, both of which have negative consequences. We obtained a dataset of 35,875 patients from the screening arm of the National Cancer Institute's Prostate, Lung, Colorectal, and Ovarian Cancer Screening Trial. We developed a pipeline to deal with imbalanced data and proposed algorithms to perform preprocessing on such datasets. We evaluated the accuracy of various machine learning algorithms in predicting high-risk prostate cancer.

A new framework combining machine learning and radiomics will help distinguish between low- and high-risk prostate cancer, according to new research published in Scientific Reports. "By rigorously and systematically combining machine learning with radiomics, our goal is to provide radiologists and clinical personnel with a sound prediction tool that can eventually translate to more effective and personalized patient care," said lead author Gaurav Pandey, PhD, of the Icahn School of Medicine at Mount Sinai, in a prepared statement. AI continues to be an instrumental tool in the diagnosis of many cancers, including cervical, uterine and lung. Pandey and colleagues developed the method to allow for radiologists to accurately identify treatment options for prostate cancer patients. This may decrease the chance for unnecessary clinical intervention.