A healthcare technology company, Avenda Health, claims that its software can identify the extent of prostate cancer more accurately than doctors. In a recent study, ten physicians evaluated 50 separate cases of prostate cancer, revealing that Avenda’s Unfold AI software achieved an accuracy rate of 84.7%, compared to the manual detection accuracy of the doctors, which ranged from 67.2% to 75.9%.
Conducted in collaboration with UCLA Health and published in the Journal of Urology, the study highlighted that the incorporation of AI for cancer contouring significantly improved the predictions of tumor size, making them 45 times more reliable and consistent compared to traditional methods.
Dr. Shyam Natarajan, assistant adjunct professor of urology, surgery, and bioengineering at UCLA and the senior author of the study, stated that AI assistance led to greater accuracy and consistency among doctors, allowing for better agreement on diagnosis.
Dr. Wayne Brisbane, an assistant professor of urology at the David Geffen School of Medicine at UCLA, explained that although doctors typically use MRIs to assess tumor size, some tumors are not visible on these scans. AI technology can address these limitations.
Brisbane emphasized that implementing AI in cancer treatment could result in more effective and personalized patient care, with therapies being more finely attuned to individual needs and more efficient in combating the disease. He noted that AI can exceed human capabilities in this context.
Avenda Health’s CEO, Dr. Shyam Natarajan, remarked that it is inspiring for medical professionals to see such innovations being substantiated through research and endorsed by the American Medical Association (AMA).
According to the American Cancer Society, approximately 1 in 8 men in the United States will be diagnosed with prostate cancer in their lifetime, and 1 in 44 will succumb to the disease. This year, it is projected that there will be 299,010 new prostate cancer cases in the US, with an estimated 35,250 fatalities attributed to the illness.