An AI healthcare company has claimed that its software can detect the extent of prostate cancer with greater accuracy than physicians.
Avenda Health released a study last month that involved ten doctors reviewing 50 different prostate cancer cases. Their Unfold AI software demonstrated an accuracy rate of 84.7% in detecting cancer, while the manual evaluations by the physicians ranged from 67.2% to 75.9%.
The research, conducted in collaboration with UCLA Health and published in the Journal of Urology, further revealed that AI-assisted cancer contouring predictions were 45 times more accurate and consistent than those made without AI assistance.
Shyam Natarajan, an assistant adjunct professor of urology, surgery, and bioengineering at UCLA and senior author of the study, noted that AI assistance not only improved the accuracy of diagnoses but also led to increased consistency among doctors’ assessments.
Dr. Wayne Brisbane, an assistant professor of urology at UCLA’s David Geffen School of Medicine, explained that while doctors typically rely on MRIs to determine tumor size, certain tumors can be “MRI-invisible.” He emphasized that AI can provide additional insights where MRIs may fall short.
“The overall integration of AI in cancer treatment has the potential to enhance personalized care for patients, offering treatments that are more closely aligned with individual needs and potentially more effective in combating the disease,” Brisbane stated, adding that AI can exceed human capabilities.
Dr. Shyam Natarajan, CEO of Avenda Health, expressed that it is encouraging for doctors to witness such innovations being validated through studies and acknowledged by the American Medical Association.
According to the American Cancer Society, approximately 1 in 8 men in the U.S. will receive a prostate cancer diagnosis during their lifetime, and about 1 in 44 men will succumb to the disease. This year, it is projected that there will be 299,010 new prostate cancer cases in the U.S., with an estimated 35,250 deaths attributed to the illness.