Breakthrough Blood Test Detects Early-Stage Ovarian Cancer with High Accuracy

Researchers have developed a new blood test using machine learning to detect early-stage ovarian cancer with high accuracy. This test addresses the difficulty of diagnosing the disease early due to vague symptoms often mistaken for benign conditions, offering a promising tool for timely and informed decisions.

A cutting-edge blood test has been developed by researchers to detect early-stage ovarian cancer in patients. The test, which utilizes advanced machine learning algorithms, has emerged as a potential game changer in the diagnosis of this deadly disease often mistaken for benign conditions, researchers revealed.

Ovarian cancer ranks as the fifth leading cause of cancer-related deaths among women, largely due to diagnostic delays. The newly trialed test, evaluated on blood samples from nearly 400 women, demonstrated 92% accuracy in identifying ovarian cancer at any stage. Particularly, it showed 88% accuracy for detecting Stage I or II cancer, offering significant diagnostic advancements.

AOA Dx, the Denver-based company behind the test, envisions it as a crucial tool in making rapid, informed decisions during the challenging diagnostic process faced by many women. CEO Oriana Papin-Zoghbi underlined its significance in aiding urgent clarity and improved patient outcomes in oncology care.

(With inputs from agencies.)