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Tsinghua Science and Technology 2024, 29(1): 13-33 https://doi.org/10.26599/TST.2023.9010037
Open Access | Issue | Published: 21 August 2023

The Application of Artificial Intelligence in Alzheimer’s Research

Show Author's Information Qing Zhao1,  Hanrui Xu2,  Jianqiang Li1( ),  Faheem Akhtar Rajput3,  Liyan Qiao4( )
Faculty of Information Technology, Beijing University of Technology, Beijing 100124, China
School of Medicine, Tsinghua University, Beijing 100084, China
Department of Computer Science, Sukkur IBA University, Sukkur 65200, Pakistan
Department of Neurology, Tsinghua University Yuquan Hospital, Beijing 100040, China
Keywords:
artificial intelligence, Alzheimer’s disease, treatment, computer-aided diagnosis, etiology discovery, computer-aided prognosis
Cite this article:
Zhao Q, Xu H, Li J, et al. The Application of Artificial Intelligence in Alzheimer’s Research. Tsinghua Science and Technology, 2024, 29(1): 13-33. https://doi.org/10.26599/TST.2023.9010037
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Abstract Full text About this article

Alzheimer’s disease (AD) is an irreversible and neurodegenerative disease that slowly impairs memory and neurocognitive function, but the etiology of AD is still unclear. With the explosive growth of electronic health data, the application of artificial intelligence (AI) in the healthcare setting provides excellent potential for exploring etiology and personalized treatment approaches, and improving the disease’s diagnostic and prognostic outcome. This paper first briefly introduces AI technologies and applications in medicine, and then presents a comprehensive review of AI in AD. In simple, it includes etiology discovery based on genetic data, computer-aided diagnosis (CAD), computer-aided prognosis (CAP) of AD using multi-modality data (genetic, neuroimaging and linguistic data), and pharmacological or non-pharmacological approaches for treating AD. Later, some popular publicly available AD datasets are introduced, which are important for advancing AI technologies in AD analysis. Finally, core research challenges and future research directions are discussed.


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About this article

The Application of Artificial Intelligence in Alzheimer’s Research

Show Author's information Qing Zhao1, Hanrui Xu2, Jianqiang Li1( ), Faheem Akhtar Rajput3, Liyan Qiao4( )
Faculty of Information Technology, Beijing University of Technology, Beijing 100124, China
School of Medicine, Tsinghua University, Beijing 100084, China
Department of Computer Science, Sukkur IBA University, Sukkur 65200, Pakistan
Department of Neurology, Tsinghua University Yuquan Hospital, Beijing 100040, China

Abstract

Alzheimer’s disease (AD) is an irreversible and neurodegenerative disease that slowly impairs memory and neurocognitive function, but the etiology of AD is still unclear. With the explosive growth of electronic health data, the application of artificial intelligence (AI) in the healthcare setting provides excellent potential for exploring etiology and personalized treatment approaches, and improving the disease’s diagnostic and prognostic outcome. This paper first briefly introduces AI technologies and applications in medicine, and then presents a comprehensive review of AI in AD. In simple, it includes etiology discovery based on genetic data, computer-aided diagnosis (CAD), computer-aided prognosis (CAP) of AD using multi-modality data (genetic, neuroimaging and linguistic data), and pharmacological or non-pharmacological approaches for treating AD. Later, some popular publicly available AD datasets are introduced, which are important for advancing AI technologies in AD analysis. Finally, core research challenges and future research directions are discussed.

Keywords: artificial intelligence, Alzheimer’s disease, treatment, computer-aided diagnosis, etiology discovery, computer-aided prognosis

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Received: 27 October 2022
Revised: 22 March 2023
Accepted: 27 April 2023
Published: 21 August 2023
Issue date: February 2024

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This work was partially supported by the National Key R&D Program of China (No. 2020YFB2104402) and Beijing Postdoctoral Research Foundation (No. 2022ZZ075).

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