An AI healthcare company claims that its software can identify the extent of prostate cancer more accurately than medical professionals.
Avenda Health recently published a study involving ten doctors who evaluated 50 different prostate cancer cases. The results indicated that Avenda’s Unfold AI software detected cancer with an accuracy rate of 84.7%, compared to doctors who achieved accuracy rates ranging from 67.2% to 75.9% when assessing the cases manually.
Conducted in partnership with UCLA Health and featured in the Journal of Urology, the study also revealed that AI-assisted cancer contouring provides predictions about cancer size that are 45 times more precise and consistent when compared to traditional methods.
Shyam Natarajan, an assistant adjunct professor of urology, surgery, and bioengineering at UCLA and the study’s senior author, remarked that the incorporation of AI made healthcare professionals not only more accurate but also more consistent in their assessments, leading to greater consensus among them.
Typically, doctors rely on MRI scans to determine tumor dimensions. However, some tumors are “MRI-invisible,” noted Dr. Wayne Brisbane, an assistant professor of urology at the David Geffen School of Medicine at UCLA. He added that AI proves beneficial in these instances where MRIs fall short.
Brisbane emphasized that the adoption of AI in cancer care could yield more effective and tailored treatments for patients, enhancing their success in combating the disease, as AI surpasses human capabilities in this regard.
Avenda Health CEO Dr. Shyam Natarajan expressed that witnessing such innovations being validated through research and acknowledged by the American Medical Association is empowering for physicians.
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 men will succumb to the disease. This year, an estimated 299,010 new cases of prostate cancer are expected in the U.S., with around 35,250 fatalities attributed to the illness.