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The interdisciplinary use of deep learning in this field has shown great promise and gathered considerable interest. This paper surveys deep learning literature related to Alzheimer\u2019s disease, mild cognitive impairment, and related diseases from 2010 to early 2023. We identify the major types of unsupervised, supervised, and semi-supervised methods developed for various tasks in this field, including the most recent developments, such as the application of recurrent neural networks, graph-neural networks, and generative models. We also provide a summary of data sources, data processing, training protocols, and evaluation methods as a guide for future deep learning research into Alzheimer\u2019s disease. Although deep learning has shown promising performance across various studies and tasks, it is limited by interpretation and generalization challenges. The survey also provides a brief insight into these challenges and the possible pathways for future studies.<\/jats:p>","DOI":"10.3390\/make5020035","type":"journal-article","created":{"date-parts":[[2023,6,12]],"date-time":"2023-06-12T03:02:27Z","timestamp":1686538947000},"page":"611-668","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":42,"title":["A Survey of Deep Learning for Alzheimer\u2019s Disease"],"prefix":"10.3390","volume":"5","author":[{"given":"Qinghua","family":"Zhou","sequence":"first","affiliation":[{"name":"School of Computing and Mathematical Sciences, University of Leicester, Leicester LE1 7RH, UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0745-9386","authenticated-orcid":false,"given":"Jiaji","family":"Wang","sequence":"additional","affiliation":[{"name":"School of Computing and Mathematical Sciences, University of Leicester, Leicester LE1 7RH, UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xiang","family":"Yu","sequence":"additional","affiliation":[{"name":"School of Computing and Mathematical Sciences, University of Leicester, Leicester LE1 7RH, UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Shuihua","family":"Wang","sequence":"additional","affiliation":[{"name":"School of Computing and Mathematical Sciences, University of Leicester, Leicester LE1 7RH, UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4870-1493","authenticated-orcid":false,"given":"Yudong","family":"Zhang","sequence":"additional","affiliation":[{"name":"School of Computing and Mathematical Sciences, University of Leicester, Leicester LE1 7RH, UK"},{"name":"Department of Information Systems, Faculty of Computing and Information Technology, King Abdulaziz University, Jeddah 21589, Saudi Arabia"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2023,6,9]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"122","DOI":"10.1016\/j.schres.2021.05.018","article-title":"Going deep into schizophrenia with artificial intelligence","volume":"245","author":"Estevez","year":"2022","journal-title":"Schizophr. 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