An artificial intelligence healthcare company has announced that its software can detect the extent of prostate cancer with greater accuracy than physicians.
Recently, Avenda Health conducted a study involving ten doctors who evaluated 50 different prostate cancer cases. The results showed that Avenda’s Unfold AI software achieved an accuracy rate of 84.7% in detecting cancer, while the doctors’ manual assessments ranged from 67.2% to 75.9%.
This study, conducted in collaboration with UCLA Health and published in the Journal of Urology, also indicated that when AI was used to assist in cancer contouring, predictions regarding cancer size were 45 times more accurate and consistent compared to those made without AI assistance.
Dr. Shyam Natarajan, an assistant adjunct professor of urology, surgery, and bioengineering at UCLA and the study’s senior author, noted that AI support improved both the accuracy and consistency of the doctors’ assessments, making their evaluations more aligned.
Currently, physicians often rely on MRI scans to determine tumor size, but some tumors are “MRI-invisible,” according to Dr. Wayne Brisbane, an assistant professor of urology at the David Geffen School of Medicine at UCLA. He emphasized that AI can address the shortcomings of MRI technology.
Dr. Brisbane added that the incorporation of AI in cancer treatment has the potential to enhance personalized care for patients, allowing treatments to be more effectively tailored to individual needs. He remarked that AI can surpass human capabilities in this context.
Avenda Health’s CEO, Dr. Shyam Natarajan, expressed that it is encouraging for physicians to see such innovations validated through research and acknowledged by the American Medical Association.
According to the American Cancer Society, approximately 1 in 8 men will be diagnosed with prostate cancer in their lifetime, and 1 in 44 men will die from the disease. It is projected that there will be 299,010 new cases of prostate cancer in the U.S. this year, with an estimated 35,250 fatalities resulting from the condition.