{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,30]],"date-time":"2026-10-30T21:18:17Z","timestamp":1793395097358,"version":"4.5.0"},"reference-count":44,"publisher":"MDPI AG","issue":"1","license":[{"start":{"date-parts":[[2022,12,23]],"date-time":"2022-12-23T00:00:00Z","timestamp":1671753600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"DementiaBank","award":["AG03705"],"award-info":[{"award-number":["AG03705"]}]},{"name":"DementiaBank","award":["AG05133"],"award-info":[{"award-number":["AG05133"]}]},{"name":"NIH","award":["AG03705"],"award-info":[{"award-number":["AG03705"]}]},{"name":"NIH","award":["AG05133"],"award-info":[{"award-number":["AG05133"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Brain Sciences"],"abstract":"<jats:p>There is currently no simple, widely available screening method for Alzheimer\u2019s disease (AD), partly because the diagnosis of AD is complex and typically involves expensive and sometimes invasive tests not commonly available outside highly specialized clinical settings. Here, we developed an artificial intelligence (AI)-powered end-to-end system to detect AD and predict its severity directly from voice recordings. At the core of our system is the pre-trained data2vec model, the first high-performance self-supervised algorithm that works for speech, vision, and text. Our model was internally evaluated on the ADReSSo (Alzheimer\u2019s Dementia Recognition through Spontaneous Speech only) dataset containing voice recordings of subjects describing the Cookie Theft picture, and externally validated on a test dataset from DementiaBank. The AI model can detect AD with average area under the curve (AUC) of 0.846 and 0.835 on held-out and external test set, respectively. The model was well-calibrated (Hosmer-Lemeshow goodness-of-fit p-value = 0.9616). Moreover, the model can reliably predict the subject\u2019s cognitive testing score solely based on raw voice recordings. Our study demonstrates the feasibility of using the AI-powered end-to-end model for early AD diagnosis and severity prediction directly based on voice, showing its potential for screening Alzheimer\u2019s disease in a community setting.<\/jats:p>","DOI":"10.3390\/brainsci13010028","type":"journal-article","created":{"date-parts":[[2022,12,23]],"date-time":"2022-12-23T02:36:46Z","timestamp":1671763006000},"page":"28","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":51,"title":["Artificial Intelligence-Enabled End-To-End Detection and Assessment of Alzheimer\u2019s Disease Using Voice"],"prefix":"10.3390","volume":"13","author":[{"given":"Felix","family":"Agbavor","sequence":"first","affiliation":[{"name":"School of Biomedical Engineering, Science and Health Systems, Drexel University, Philadelphia, PA 19104, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3805-1837","authenticated-orcid":false,"given":"Hualou","family":"Liang","sequence":"additional","affiliation":[{"name":"School of Biomedical Engineering, Science and Health Systems, Drexel University, Philadelphia, PA 19104, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2022,12,23]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"365","DOI":"10.2165\/00002512-199915050-00004","article-title":"Worldwide Prevalence and Incidence of Dementia","volume":"15","author":"Fratiglioni","year":"1999","journal-title":"Drugs Aging"},{"key":"ref_2","unstructured":"Jameson, J.L., Fauci, A.S., Kasper, D.L., Hauser, S.L., Longo, D.L., and Loscalzo, J. 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