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Artificial intelligence (AI) continues to make transformative strides across industries, with healthcare leading the charge. A groundbreaking new study reveals that machine learning models can effectively and affordably identify women experiencing severe subjective cognitive decline during the menopause transition, paving the way for improved management of cognitive health.
The study, published in Menopause, highlights the potential of AI in addressing one of menopause’s most concerning symptoms—cognitive decline. Subjective cognitive decline refers to a person’s perceived deterioration in memory or cognitive function, which not only diminishes quality of life but may also signal an increased risk for severe neurodegenerative conditions such as Alzheimer’s disease.
Breaking New Ground in Cognitive Health
The research involved over 1,200 women navigating menopause and focused on using machine learning to develop a predictive model for severe subjective cognitive decline. Unlike traditional diagnostic methods—often reliant on costly and complex tests like brain imaging or laboratory indicators—this model is based on simple questionnaires. These include variables such as sociodemographic data, work and lifestyle factors, menstrual history, and mental health indicators.
Dr. Stephanie Faubion, medical director for The Menopause Society, emphasized the significance of these findings:
“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.”
Simplifying and Enhancing Early Detection
Cognitive decline has typically been studied in the context of dementia, which leaves few options for intervention. However, subjective cognitive decline, while not always a precursor to long-term cognitive impairment, offers a critical window for early action.
The machine learning approach not only simplifies the detection process but also reduces costs, making it more accessible for widespread clinical use. By identifying patterns within complex datasets, AI provides a reliable tool for healthcare professionals to pinpoint at-risk individuals and address modifiable risk factors such as hypertension, obesity, and depression.
Looking Ahead
The study authors emphasize the need for further research to validate these findings and expand the model’s predictive capabilities. Incorporating objective cognitive measures and conducting longitudinal studies could deepen understanding of the relationship between menopause and cognitive health.
“These findings provide novel guidance for interventions designed to preserve cognitive health in women undergoing the menopause transition,” the researchers noted.
As AI continues to revolutionize healthcare, this pilot study marks a significant step toward personalized, preventive care for women during one of life’s most transformative stages.
For more details, refer to the study: Using machine learning models to identify severe subjective cognitive decline and related factors in nurses during the menopause transition: a pilot study, Menopause (2025). DOI: 10.1097/GME.00000000000002500.
