AI Takes Prostate Cancer Detection to the Next Level: What You Need to Know

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An artificial intelligence healthcare company has announced that its software can identify the extent of prostate cancer with greater accuracy than medical professionals.

Avenda Health published a study last month involving ten doctors who evaluated 50 prostate cancer cases each. The findings revealed that Avenda’s Unfold AI software detected cancer with an accuracy of 84.7%, while the physicians’ manual assessments ranged from 67.2% to 75.9%.

Conducted in collaboration with UCLA Health and featured in the Journal of Urology, the study also indicated that AI-assisted cancer contouring predictions for tumor size were 45 times more accurate and consistent compared to traditional methods.

According to Shyam Natarajan, assistant adjunct professor of urology at UCLA and senior author of the study, the integration of AI assistance improved both the accuracy and consistency of doctors’ evaluations, leading to a higher level of agreement among physicians using the AI tools.

Doctors typically rely on MRI scans to gauge tumor size; however, some tumors can remain undetectable on MRI, noted Dr. Wayne Brisbane, an assistant professor of urology at UCLA. He emphasized that AI technology provides support in cases where MRI fails to yield results.

Brisbane added that incorporating AI in cancer treatment could potentially result in more effective and personalized patient care, with treatment plans that are more aligned with individual needs and have better chances of success against the disease.

Avenda Health CEO Dr. Shyam Natarajan expressed that it is “empowering for physicians to see this kind of innovation being validated through studies and recognized by the AMA.”

The American Cancer Society estimates that approximately 1 in 8 men in the US will be diagnosed with prostate cancer, and 1 in 44 men will succumb to the illness. This year alone, around 299,010 new cases of prostate cancer are expected in the US, with an estimated 35,250 deaths resulting from the disease.

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