AI Revolutionizes Prostate Cancer Detection with Unprecedented Accuracy

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Avenda Health, an AI healthcare company, claims its software can identify the extent of prostate cancer more accurately than traditional methods used by doctors.

In a recent study involving ten physicians who evaluated 50 different prostate cancer cases each, Avenda’s Unfold AI software achieved an accuracy rate of 84.7% in detecting cancer. In contrast, the doctors’ manual assessments varied between 67.2% and 75.9% accuracy.

The study, which was conducted in collaboration with UCLA Health and published in the Journal of Urology, also highlighted that using AI for cancer contouring resulted in predictions of tumor size being 45 times more accurate and consistent compared to assessments made without AI assistance.

Shyam Natarajan, an assistant adjunct professor of urology, surgery, and bioengineering at UCLA and the study’s senior author, noted that AI-assisted evaluations led to greater accuracy and consistency among physicians, improving agreement on cases.

Physicians typically rely on MRIs to assess tumor size; however, some tumors are not visible through MRI, as explained by Dr. Wayne Brisbane, an assistant professor of urology at UCLA’s David Geffen School of Medicine. He emphasized that AI can fill in the gaps where MRIs are ineffective.

Dr. Brisbane stated that the integration of AI in cancer treatment could lead to more effective and personalized care, tailoring treatments to meet individual patient needs more successfully.

Avenda Health’s CEO, Dr. Shyam Natarajan, expressed that it is empowering for physicians to witness such innovations being validated through research and acknowledged by the American Medical Association.

According to the American Cancer Society, approximately 1 in 8 men in the U.S. will be diagnosed with prostate cancer during their lifetimes, and 1 in 44 men will succumb to the disease. This year, it is estimated that there will be 299,010 new prostate cancer cases in the U.S., with 35,250 deaths attributed to the disease.

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