AI Revolutionizes Prostate Cancer Detection: A New Frontier in Accuracy

by

in

An artificial intelligence healthcare company has announced that its software can more accurately assess the extent of prostate cancer compared to traditional methods used by doctors.

Avenda Health’s recent study, which involved ten physicians evaluating 50 prostate cancer cases each, demonstrated that its Unfold AI software achieved a cancer detection accuracy of 84.7%. In contrast, physicians’ manual detection accuracy varied between 67.2% and 75.9%.

Conducted in collaboration with UCLA Health and published in the Journal of Urology, the study also revealed that AI-assisted cancer contouring predictions for tumor size were 45 times more accurate and consistent than manual methods.

Shyam Natarajan, an assistant adjunct professor of urology, surgery, and bioengineering at UCLA and the study’s senior author, stated that AI assistance improved doctors’ accuracy and consistency, leading to more agreement among them during assessments.

Typically, doctors rely on MRIs to gauge tumor size; however, some tumors are not visible on MRIs. Dr. Wayne Brisbane, an assistant professor of urology at the David Geffen School of Medicine at UCLA, noted that AI can provide valuable insights where MRIs are insufficient.

Brisbane expressed optimism about the potential of AI to enhance cancer treatment, promoting more effective and personalized patient care tailored to individual needs. He highlighted that AI’s capabilities can exceed those of humans in certain aspects.

Dr. Shyam Natarajan, CEO of Avenda Health, conveyed excitement about the validation of such innovations through research and recognition from the American Medical Association.

According to the American Cancer Society, approximately 1 in 8 men will face a prostate cancer diagnosis in their lifetime, and 1 in 44 men will succumb to the disease. It is projected that there will be 299,010 new prostate cancer cases in the US this year, with 35,250 deaths attributed to the condition.

Popular Categories


Search the website