AI Outperforms Doctors in Prostate Cancer Detection: Study Reveals Shocking Accuracy

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An artificial intelligence healthcare company claims that its software can more accurately assess the extent of prostate cancer than human doctors.

Avenda Health conducted a study last month involving ten physicians who each evaluated 50 prostate cancer cases. The company’s Unfold AI software achieved an accuracy rate of 84.7% in detecting cancer, while the accuracy range for the doctors was between 67.2% and 75.9%.

The research, conducted in collaboration with UCLA Health and published in the Journal of Urology, highlighted that AI-assisted cancer contouring led to predictions of tumor size being 45 times more precise and consistent compared to traditional methods.

According to Shyam Natarajan, an assistant adjunct professor of urology, surgery, and bioengineering at UCLA and senior author of the study, the integration of AI assistance improved both the accuracy and consistency of the doctors’ assessments, leading to greater agreement among them.

Typically, physicians rely on MRI scans to determine tumor size, but some tumors remain “MRI-invisible,” noted Dr. Wayne Brisbane, an assistant professor of urology at UCLA’s David Geffen School of Medicine. He emphasized that AI provides critical support where MRI scans fall short.

Dr. Brisbane added that the implementation of AI in cancer treatment could facilitate more effective and personalized care for patients, allowing for treatments that are better suited to individual needs and improving the likelihood of successful outcomes.

Avenda Health’s CEO, Dr. Shyam Natarajan, expressed his satisfaction with the validation of their innovation through this research, which has garnered recognition from the American Medical Association.

According to the American Cancer Society, approximately 1 in 8 men will be diagnosed with prostate cancer in their lifetime, and 1 in 44 will succumb to the illness. It is estimated that there will be 299,010 new cases of prostate cancer in the US this year, with 35,250 expected fatalities from the disease.

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