Assessing the accuracy of survival machine learning and traditional statistical models for Alzheimer's disease prediction over time: a study on the ADNI cohort

Abstract Background Mild cognitive impairment (MCI) represents a transitional stage to Alzheimer's disease (AD), making progression prediction crucial for timely intervention. Predictive models integrating clinical, laboratory, and survival data can enhance early diagnosis and treatment decisions. W...

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Detalhes bibliográficos

Principais autores:	Sardar Jahani, Ghodratollah Roshanaei, Leili Tapak, for the Alzheimer’s Disease Neuroimaging Initiative
Formato:	Artigo
Idioma:	Inglês
Publicado em:	BMC 2025-11-01
coleção:	BMC Medical Research Methodology
Assuntos:	Alzheimer's disease Survival analysis Machine learning Random survival forest
Acesso em linha:	https://doi.org/10.1186/s12874-025-02689-w
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