New test finds ovarian cancer early, thanks to AI

women’s health

by alex mitchell

Scientists say they have developed an early screening test that can detect ovarian cancer with great accuracy, thanks to breakthroughs in artificial intelligence.

John MacDonald, professor emeritus at Georgia Tech, said the machine learning approach, which is 93% accurate, “represents a promising new direction in the early detection of ovarian cancer, and perhaps other cancers.” Ta.

Georgia Tech researchers describe ovarian cancer as a “silent killer,” and early detection is especially important because it usually has no symptoms at first and is rarely detected during routine pelvic exams. is.

Georgia Tech scientists say a woman’s metabolic profile can be used to determine her exact likelihood of developing ovarian cancer.

“This personalized approach to cancer diagnosis is more clinically informative and accurate than traditional binary (yes/no) testing,” McDonald said.

Ovarian cancer is the leading cause of cancer death in women.

The American Cancer Society reports that approximately 1 in 87 women will develop ovarian cancer and 1 in 130 will likely die from ovarian cancer.

Warning signs include bloating, abdominal pain, difficulty eating, and frequent urination.

Determining whether a woman has ovarian cancer involves a rectovaginal exam to identify abnormalities, a transvaginal ultrasound to obtain pictures of the pelvis, and/or measuring the presence of certain proteins. You may need a CA-125 blood test to

If treated early, the five-year survival rate is over 90%, Georgia Tech noted.

The university’s research results were published online in March in the journal Gynamic Oncology.

The researchers focused on metabolites (molecules produced in chemical processes) in the blood.

Typically, potentially game-changing metabolites are identified as broad groups rather than as individual entities, co-author Jeffrey Skolnick explained.

Less than 7% of them in the blood have been chemically characterized, but by combining machine learning and mass spectrometry analytical techniques, researchers are paving the way to diagnosing ovarian cancer. co-author Ban Dongjo added. .

He said the new approach allows for “accurate ovarian cancer diagnosis” as thousands of metabolites “can be detected easily and accurately.”

“Clearly, there is a great need for accurate early diagnostic tests for this insidious disease,” McDonald added.

The researchers are optimistic that the new method, which was tested on 564 women, could lead to early screening for other types of cancer.