{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,25]],"date-time":"2026-09-25T06:47:22Z","timestamp":1790318842422,"version":"4.1.0"},"reference-count":125,"publisher":"MDPI AG","issue":"12","license":[{"start":{"date-parts":[[2024,6,17]],"date-time":"2024-06-17T00:00:00Z","timestamp":1718582400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Institute of Information &amp; communications Technology Planning &amp; Evaluation (IITP) grant funded by the Korea government(MSIT)","award":["1711160571"],"award-info":[{"award-number":["1711160571"]}]},{"name":"Institute of Information &amp; communications Technology Planning &amp; Evaluation (IITP) grant funded by the Korea government(MSIT)","award":["RS-2022-00166402"],"award-info":[{"award-number":["RS-2022-00166402"]}]},{"name":"Institute of Information &amp; communications Technology Planning &amp; Evaluation (IITP) grant funded by the Korea government(MSIT)","award":["RS-2023-00256517"],"award-info":[{"award-number":["RS-2023-00256517"]}]},{"name":"National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIT)","award":["1711160571"],"award-info":[{"award-number":["1711160571"]}]},{"name":"National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIT)","award":["RS-2022-00166402"],"award-info":[{"award-number":["RS-2022-00166402"]}]},{"name":"National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIT)","award":["RS-2023-00256517"],"award-info":[{"award-number":["RS-2023-00256517"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Diagnostics"],"abstract":"<jats:p>Alzheimer\u2019s disease (AD) is a neurological disorder that significantly impairs cognitive function, leading to memory loss and eventually death. AD progresses through three stages: early stage, mild cognitive impairment (MCI) (middle stage), and dementia. Early diagnosis of Alzheimer\u2019s disease is crucial and can improve survival rates among patients. Traditional methods for diagnosing AD through regular checkups and manual examinations are challenging. Advances in computer-aided diagnosis systems (CADs) have led to the development of various artificial intelligence and deep learning-based methods for rapid AD detection. This survey aims to explore the different modalities, feature extraction methods, datasets, machine learning techniques, and validation methods used in AD detection. We reviewed 116 relevant papers from repositories including Elsevier (45), IEEE (25), Springer (19), Wiley (6), PLOS One (5), MDPI (3), World Scientific (3), Frontiers (3), PeerJ (2), Hindawi (2), IO Press (1), and other multiple sources (2). The review is presented in tables for ease of reference, allowing readers to quickly grasp the key findings of each study. Additionally, this review addresses the challenges in the current literature and emphasizes the importance of interpretability and explainability in understanding deep learning model predictions. The primary goal is to assess existing techniques for AD identification and highlight obstacles to guide future research.<\/jats:p>","DOI":"10.3390\/diagnostics14121281","type":"journal-article","created":{"date-parts":[[2024,6,17]],"date-time":"2024-06-17T11:14:16Z","timestamp":1718622856000},"page":"1281","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":51,"title":["Deep Learning for Alzheimer\u2019s Disease Prediction: A Comprehensive Review"],"prefix":"10.3390","volume":"14","author":[{"given":"Isra","family":"Malik","sequence":"first","affiliation":[{"name":"Department of Computer Science, COMSATS University Islamabad, Wah Campus, Wah Cantt 44000, Pakistan"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4946-4167","authenticated-orcid":false,"given":"Ahmed","family":"Iqbal","sequence":"additional","affiliation":[{"name":"Department of Computer Science, Sir Syed Case Institute of Technology, Islamabad 45230, Pakistan"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0002-9386","authenticated-orcid":false,"given":"Yeong Hyeon","family":"Gu","sequence":"additional","affiliation":[{"name":"Department of Artificial Intelligence and Data Science, College of AI Convergence, Daeyang AI Center, Sejong University, Seoul 05006, Republic of Korea"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4457-4407","authenticated-orcid":false,"given":"Mugahed A.","family":"Al-antari","sequence":"additional","affiliation":[{"name":"Department of Artificial Intelligence and Data Science, College of AI Convergence, Daeyang AI Center, Sejong University, Seoul 05006, Republic of Korea"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2024,6,17]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"73373","DOI":"10.1109\/ACCESS.2019.2920011","article-title":"Ensembles of Patch-Based Classifiers for Diagnosis of Alzheimer Diseases","volume":"7","author":"Ahmed","year":"2019","journal-title":"IEEE Access"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"984","DOI":"10.1109\/JBHI.2013.2285378","article-title":"Multiple Kernel Learning in the Primal for Multimodal Alzheimer\u2019s Disease Classification","volume":"18","author":"Liu","year":"2014","journal-title":"IEEE J. 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