Review
Version 1
This version is not peer-reviewed
Potential Applications of Artificial Intelligence in Clinical Trials for Alzheimer’s Disease
Version 1
: Received: 6 October 2021 / Approved: 8 October 2021 / Online: 8 October 2021 (11:31:14 CEST)
How to cite: Seo, Y.; Jang, H.; Lee, H. Potential Applications of Artificial Intelligence in Clinical Trials for Alzheimer’s Disease. Preprints 2021, 2021100139 Seo, Y.; Jang, H.; Lee, H. Potential Applications of Artificial Intelligence in Clinical Trials for Alzheimer’s Disease. Preprints 2021, 2021100139
Abstract
Clinical trials for Alzheimer’s disease (AD) face multiple challenges, such as the high screen failure rate and even allocation of heterogeneous participants. Artificial intelligence (AI), which has become a potent tool of modern science with the expansion in the volume, variety, and velocity of biological data, offers promising potential to address these issues in AD clinical trials. In this review, we introduce the current status of AD clinical trials and topic of machine learning. Then, a comprehensive review is focused on the potential applications of AI in the steps of AD clinical trials, including the prediction of AD biomarkers and differential diagnosis of AD in the prescreen during eligibility assessment and the likelihood stratification of patients who will progress to AD dementia and fast cognitive decline group from the slow decline group in randomization. Finally, this review provides challenges, developments and the future outlook on the integration of AI into AD clinical trials.
Keywords
Alzheimer’s disease; artificial intelligence; clinical trials; eligibility assessment; randomization
Subject
Medicine and Pharmacology, Neuroscience and Neurology
Copyright: This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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