AI Outperforms Doctors in Detecting Prostate Cancer: A Revolutionary Study

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An AI healthcare company has announced that its software can more accurately assess the extent of prostate cancer than human doctors.

Avenda Health recently published a study that involved ten physicians evaluating 50 different prostate cancer cases each. The findings revealed that Avenda’s Unfold AI software achieved an accuracy rate of 84.7% in cancer detection, compared to the manual detection rates by doctors, which ranged from 67.2% to 75.9%.

Conducted in collaboration with UCLA Health and featured in the Journal of Urology, the study also highlighted that AI-assisted cancer contouring resulted in predictions of tumor size being 45 times more accurate than traditional methods.

Shyam Natarajan, a senior author of the study and assistant adjunct professor of urology, surgery, and bioengineering at UCLA, noted that the integration of AI not only improved diagnostic accuracy but also enhanced consistency among doctors, who tended to agree more when utilizing AI tools.

According to Dr. Wayne Brisbane, an assistant professor of urology at UCLA’s David Geffen School of Medicine, while doctors typically rely on MRIs to evaluate tumor sizes, some tumors are undetectable via this imaging method, and AI can effectively address these limitations.

Brisbane emphasized that the incorporation of AI in cancer care could pave the way for more effective and personalized patient treatments. He stated that AI has the potential to exceed human capabilities in this domain.

Dr. Shyam Natarajan, CEO of Avenda Health, expressed his approval at the validation of their technology through academic research and recognition from the American Medical Association.

Statistics from the American Cancer Society indicate that approximately 1 in 8 men will be diagnosed with prostate cancer during their lifetime, with 1 in 44 men succumbing to the disease. This year alone, it is estimated that there will be 299,010 new cases of prostate cancer in the U.S., with 35,250 expected fatalities.

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