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Global, regional, and national burden of major depressive disorders in adults aged 60 years and older from 1990 to 2021, with projections of prevalence to 2050: Analyses from the Global Burden of Disease Study 2021.

J Affect Disord

January 2025

Department of Epidemiology and Biostatistics, School of Public Health, Peking University, No.38, Xueyuan Road, Haidian District, Beijing 100191, China; Key Laboratory of Epidemiology of Major Diseases, Peking University, Ministry of Education, No.38, Xueyuan Road, Haidian District, Beijing 100191, China; Institute for Global Health and Development, Peking University, No.5 Yiheyuan Road, Haidian District, Beijing 100871, China; Global Center for Infectious Disease and Policy Research & Global Health and Infectious Diseases Group, Peking University, No.38, Xueyuan Road, Haidian District, Beijing 100191, China. Electronic address:

Aims: To estimate the burden of major depressive disorder (MDD) among older adults and project its prevalence through 2050.

Methods: Using data from the Global Burden of Disease Study 2021, we calculated age-standardized rates (ASRs) for the incidence, prevalence, and years lived with disability (YLDs) of MDD among people aged ≥60 years from 1990 to 2021. Trends were analyzed using average annual percentage changes (AAPCs).

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Eur J Nucl Med Mol Imaging

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Department of Nuclear Medicine & PET Center, Huashan Hospital, Fudan University, Shanghai, China.

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Artificial intelligence (AI) and machine learning (ML) are driving innovation in biosciences and are already affecting key elements of medical scholarship and clinical care. Many schools of medicine are capitalizing on the promise of these new technologies by establishing academic units to catalyze and grow research and innovation in AI/ML. At Stanford University, we have developed a successful model for an AI/ML research center with support from academic leaders, clinical departments, extramural grants, and industry partners.

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