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Thieme Medical Publishers.","DOI":"10.1055\/s-0035-1555115"},{"issue":"1","key":"10.1016\/j.eswa.2023.119541_b0185","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1186\/s13195-021-00768-w","article-title":"Assessing individual-level change in dementia research: A review of methodologies","volume":"13","author":"Murray","year":"2021","journal-title":"Alzheimer's Research & Therapy"},{"issue":"3","key":"10.1016\/j.eswa.2023.119541_b0190","doi-asserted-by":"crossref","first-page":"303","DOI":"10.1001\/archneur.56.3.303","article-title":"Mild cognitive impairment: Clinical characterization and outcome","volume":"56","author":"Petersen","year":"1999","journal-title":"Archives of Neurology"},{"issue":"3","key":"10.1016\/j.eswa.2023.119541_b0195","doi-asserted-by":"crossref","first-page":"323","DOI":"10.1093\/geronj\/37.3.323","article-title":"Measurement of functional activities in older adults in the community","volume":"37","author":"Pfeffer","year":"1982","journal-title":"Journal of Gerontology"},{"key":"10.1016\/j.eswa.2023.119541_b0200","unstructured":"Prince, M. 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(2019). A parameter-efficient deep learning approach to predict conversion from mild cognitive impairment to alzheimer's disease. 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