Classification of Alzheimer's disease and frontotemporal dementia using routine clinical and cognitive measures across multicentric underrepresented samples: a cross sectional observational study

Marcelo Adrián Maito,Hernando Santamaría-García,Sebastián Moguilner,Katherine L Possin,María E Godoy,José Alberto Avila-Funes,María I Behrens, Ignacio L Brusco,Martín A Bruno,Juan F Cardona,Nilton Custodio,Adolfo M García,Shireen Javandel,Francisco Lopera,Diana L Matallana,Bruce Miller,Maira Okada de Oliveira,Stefanie D Pina-Escudero,Andrea Slachevsky, Ana L Sosa Ortiz,Leonel T Takada, Enzo Tagliazuchi,Victor Valcour,Jennifer S Yokoyama,Agustín Ibañez

The Lancet Regional Health - Americas（2023）

引用 14|浏览38

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摘要

This work was supported by the Multi-Partner Consortium to Expand Dementia Research in Latin America (ReDLat), funded by NIA/NIH (R01AG057234), Alzheimer's Association (SG-20-725707-ReDLat), Rainwater Foundation, Takeda (CW2680521), Global Brain Health Institute; as well as CONICET; FONCYT-PICT (2017-1818, 2017-1820); PIIECC, Facultad de Humanidades, Usach; Sistema General de Regalías de Colombia (BPIN2018000100059), Universidad del Valle (CI 5316); ANID/FONDECYT Regular (1210195, 1210176, 1210176); ANID/FONDAP (15150012); ANID/PIA/ANILLOS ACT210096; and Alzheimer's Association GBHI ALZ UK-22-865742.

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关键词

Alzheimer's Disease,Frontotemporal dementia,Underrepresented samples,Machine learning

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