An examiner checks the results made by an artificial intelligence (AI) model for blood cell testing in a laboratory at Xinqiao Hospital under the Army Medical University in southwest China's Chongqing, Feb. 14, 2023. (Xinqiao Hospital/Handout via Xinhua)
These data reflect the untapped potential of incorporating AI/ML in electronic health records and other clinical settings to improve the diagnosis and care of women with PCOS.
LOS ANGLES, Sept. 19 (Xinhua) -- Artificial intelligence (AI) and machine learning (ML) can effectively detect and diagnose polycystic ovary syndrome (PCOS), which is the most common hormone disorder among women, typically between ages 15 and 45, according to a new study by the U.S. National Institutes of Health.
PCOS is the most common endocrinopathy in women of reproductive age and remains widely underdiagnosed leading to significant morbidity, according to the study published on Monday.
The researchers performed a systematic review of literature to identify the utility of AI and ML in the diagnosis or classification of PCOS. They found AI and ML could provide a high diagnostic and classification performance in detecting PCOS, thereby providing an avenue for early diagnosis of this disorder.
"PCOS can be challenging to diagnose given its overlap with other conditions," said Skand Shekhar, senior author of the study and assistant research physician and endocrinologist at the U.S. National Institute of Environmental Health Sciences.
"These data reflect the untapped potential of incorporating AI/ML in electronic health records and other clinical settings to improve the diagnosis and care of women with PCOS," Shekhar said.
Study authors suggested integrating large population-based studies with electronic health datasets and analyzing common laboratory tests to identify sensitive diagnostic biomarkers that can facilitate the diagnosis of PCOS. ■