AI Revolutionizes Prostate Cancer Detection: Is It More Reliable Than Traditional Methods?

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An AI healthcare company, Avenda Health, claims that its software can more accurately determine the scope of prostate cancer compared to traditional methods used by doctors.

In a recent study featuring ten physicians who each evaluated 50 prostate cancer cases, Avenda’s Unfold AI software achieved a detection accuracy rate of 84.7%. In contrast, the accuracy of the participating doctors ranged from 67.2% to 75.9%. This research was conducted in collaboration with UCLA Health and published in the Journal of Urology.

The findings also revealed that integrating AI for cancer contouring resulted in predictions of tumor size being 45 times more precise compared to conventional methods. Shyam Natarajan, an assistant adjunct professor at UCLA and the study’s senior author, stated that the use of AI assistance improved both accuracy and consistency among doctors, leading to greater agreement in their assessments.

Doctors typically rely on MRIs to evaluate tumor sizes; however, some tumors remain “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 provide insight where MRIs may fall short.

Dr. Brisbane remarked that embracing AI in cancer treatment could facilitate more effective and personalized patient care, allowing for tailored treatments that are more likely to succeed against the disease. He noted that AI’s capabilities extend beyond what humans can achieve.

Avenda Health’s CEO, Dr. Natarajan, expressed that seeing such innovative solutions validated through research and recognized by the AMA is motivating for physicians.

According to the American Cancer Society, about 1 in 8 men will be diagnosed with prostate cancer in their lifetime, and 1 in 44 men will ultimately succumb to the illness. It is projected that there will be 299,010 new prostate cancer cases in the United States this year, with an estimated 35,250 deaths resulting from the disease.

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