New AI Model Detects Early Signs of Cognitive Decline in Menopausal Women: Study Finds
Advertisement
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.
Our comments section is governed by our Comments Policy . By posting comments at Medical Dialogues you automatically agree with our Comments Policy , Terms And Conditions and Privacy Policy .
Disclaimer: This website is primarily for healthcare professionals. The content here does not replace medical advice and should not be used as medical, diagnostic, endorsement, treatment, or prescription advice. Medical science evolves rapidly, and we strive to keep our information current. If you find any discrepancies, please contact us at corrections@medicaldialogues.in. Read our Correction Policy here. Nothing here should be used as a substitute for medical advice, diagnosis, or treatment. We do not endorse any healthcare advice that contradicts a physician's guidance. Use of this site is subject to our Terms of Use, Privacy Policy, and Advertisement Policy. For more details, read our Full Disclaimer here.
NOTE: Join us in combating medical misinformation. If you encounter a questionable health, medical, or medical education claim, email us at factcheck@medicaldialogues.in for evaluation.