AI-Outshines Doctors in Prostate Cancer Detection: A Game Changer?

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Avenda Health, an AI healthcare company, claims its software can identify the extent of prostate cancer with greater accuracy than traditional methods used by doctors. A recent study involving ten physicians, each evaluating 50 prostate cancer cases, revealed that Avenda’s Unfold AI software achieved an accuracy rate of 84.7%. In comparison, the doctors’ manual assessments ranged from 67.2% to 75.9% accuracy.

Conducted in collaboration with UCLA Health and published in the Journal of Urology, the study demonstrated that AI-assisted cancer contouring predictions of tumor size were 45 times more precise and consistent than those made without AI.

Shyam Natarajan, an assistant adjunct professor of urology, surgery, and bioengineering at UCLA and the study’s senior author, noted that using AI assistance led to greater accuracy and consistency among doctors, who showed improved agreement when utilizing AI technologies.

Doctors usually rely on MRIs to assess tumor size; however, some tumors are not visible through MRI scans. Dr. Wayne Brisbane, an assistant professor of urology at UCLA, emphasized that AI can step in where MRI fails to deliver results.

Furthermore, Dr. Brisbane remarked that incorporating AI into cancer treatment could facilitate more effective and personalized care for patients, enabling more tailored and successful treatment options. He stated that AI has the potential to surpass human capabilities in cancer detection and treatment.

Dr. Shyam Natarajan, CEO of Avenda Health, expressed that it is encouraging for physicians to see such innovative technology being validated through research and recognized by the American Medical Association.

According to the American Cancer Society, one in eight men in the United States will receive a prostate cancer diagnosis in their lifetime, and one in 44 men will die from the disease. It is projected that there will be 299,010 new cases of prostate cancer in the US this year, with 35,250 fatalities attributed to the disease.

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