MENOPRED is an innovative, low-cost, non-invasive digital screening platform designed to estimate dementia risk in women during the menopausal transition and postmenopausal period. By integrating reproductive history and hormone profiles with interpretable machine learning algorithms, the project aims to provide a sex-specific tool for early risk assessment that can be used in primary healthcare settings. The platform will generate individualized risk reports, helping clinicians identify women at higher risk of dementia before symptoms appear, improving early intervention opportunities and reducing reliance on expensive and invasive diagnostic procedures. The project leverages evidence from the ReDLat and REDLINC cohorts and seeks to advance a validated prototype from TRL 2 to TRL 4, with potential for future implementation across Chile and Latin America.
PIs: Claudia Duran-Aniotz, Rolando de la Cruz, Hernán Hernández, Agustín Ibáñez, Carolina González, Andrea Slachevsky & Juan Enrique Blumel
Support: ANID FONDEF IDeA I+D
