A healthcare technology company, Avenda Health, claims that its artificial intelligence software is more effective at detecting prostate cancer than trained physicians.
Last month, Avenda published a study involving ten doctors who each evaluated 50 prostate cancer cases. The findings revealed that Avenda’s Unfold AI software achieved an accuracy rate of 84.7% in detecting cancer, while the physicians’ manual assessments ranged from 67.2% to 75.9% accuracy.
This study was conducted in collaboration with UCLA Health and published in the Journal of Urology. It highlighted that AI-assisted cancer contouring predictions are 45 times more accurate and consistent compared to traditional methods.
Shyam Natarajan, an assistant adjunct professor of urology, surgery, and bioengineering at UCLA and the study’s senior author, stated that the integration of AI not only improved the accuracy of doctors’ assessments but also increased agreement among them when using the AI tool.
Typically, physicians rely on MRI scans to measure tumor sizes; however, some tumors are undetectable through MRIs, as noted by Dr. Wayne Brisbane, an assistant professor of urology at UCLA’s David Geffen School of Medicine. He emphasized that AI fills in the gaps where MRIs may fall short.
Dr. Brisbane expressed confidence in AI’s potential to enhance cancer treatment, suggesting that it could lead to more personalized and effective care for patients, aligning treatments more closely with individual needs. He remarked that AI capabilities may surpass those of human professionals.
Avenda Health’s CEO, Dr. Shyam Natarajan, praised the validation of their innovative approach through research and its acknowledgment by the American Medical Association (AMA).
According to the American Cancer Society, approximately one in eight men in the United States will be diagnosed with prostate cancer in their lifetime, and one in 44 will succumb to the disease. For 2023, it is estimated that there will be 299,010 new prostate cancer cases in the U.S., with 35,250 fatalities anticipated due to the illness.