AI for Prostate Cancer Diagnosis
Paige Prostate: AI-based software to identify Prostate Cancer
University of Oxford
AI-based software called Paige Prostate helps pathologists identify suspicious areas in digitally scanned images from prostate biopsies. Pathologists are health care providers that analyze tissue samples. The software finds areas in the biopsy image that are likely to be cancerous but weren’t spotted by the pathologist.
When a pathologist reviews the areas identified by Paige Prostate, they also think about your medical history and the need for more testing of the tissue sample before they make a diagnosis.
Paige Prostate will be able to give more information about prostate cancer, including detecting a tumour, its size and how severe it is, enabling clinicians to make treatment more specific and more targeted.
Northeastern University: new web-based tool utilizing AI can help pathologists detect prostate cancer faste
Researchers at Northeastern’s Roux Institute in Portland, Maine, say the new tool can help expedite the diagnosis.
Current methods involve doctors reviewing biopsy slides manually looking for abnormality in the organ. That process can take an hour. The new tool takes just seconds, researchers say.
This work will provide a more accurate and timelier diagnosis and grading than the manual existing process in prostate cancer diagnosis.
The web tool can be accessed using any internet browser. Its interface was designed to be quick and easy to use, allowing pathologists to upload biopsy scans in just a few clicks, Amal explains. (The tool isn’t FDA-approved yet, and the web tool is currently being hosted on the university’s servers.)
U.S. Department of Veterans Affairs: to develop an AI algorithm to predict prostate cancer spread
As part of a new research study that began July 1, five Department of Veterans Affairs medical centers are working together to develop an Artificial Intelligence algorithm that can predict if a case of prostate cancer might spread to other parts of the body onLoad="get_data()".
Eventually expanding to 14 sites, the study will analyze data from more than 5,000 Veterans diagnosed with high-risk prostate cancer who have undergone initial treatment.
The new method will use diagnostic images (like MRIs), high resolution scans of prostate biopsies, and social determinants of health – which are variables like income and geographic location — to detect patterns indicative of aggressive prostate cancer.