New AI Model Detects Early Signs of Cognitive Decline in Menopausal Women: Study Finds
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A new study suggests that machine learning models can more quickly and affordably identify women with severe subjective cognitive decline during the menopause transition, effectively opening the door to better management of cognitive health. Results of the study are published online in Menopause.
Subjective cognitive decline refers to a person’s perceived decline in memory or other cognitive functions.
Existing testing for cognitive performance is largely based on models typically incorporating various laboratory indicators such as blood glucose, blood lipids, and brain imaging. The complexity and high cost of these models often make them impractical to implement in a clinical setting. In comparison, questionnaire-based models offer a simpler and more cost-effective alternative. These models rely on a number of independent variables, including sociodemographic, work-related, menstrual-related, lifestyle-related, and mental health-related factors.
In this latest study involving more than 1,200 women undergoing the menopause transition, researchers were able to develop and validate a machine learning model for identifying women experiencing severe subjective cognitive decline, along with associated factors.
These findings provide a novel guidance for interventions designed to preserve cognitive health in women undergoing the menopause transition. Additional research is needed to validate these results and identify additional potential influencing factors.
“This study highlights how the use of machine learning can be employed to identify women experiencing severe subjective cognitive decline during the menopause transition and potential associated factors. Early identification of high-risk persons may allow for targeted interventions to protect cognitive health. Future studies involving objective measures of cognition and longitudinal follow-up are crucial to better understanding these associations,” says Dr. Stephanie Faubion, medical director for The Menopause Society.
Reference: DOI: 10.1097/GME.0000000000002500
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