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A multimodal deep learning approach for the prediction of cognitive decline and its effectiveness in clinical trials for Alzheimer’s disease

Medicine and Health

A multimodal deep learning approach for the prediction of cognitive decline and its effectiveness in clinical trials for Alzheimer’s disease

C. Wang, H. Tachimori, et al.

This innovative study, conducted by Caihua Wang, Hisateru Tachimori, Hiroyuki Yamaguchi, Atsushi Sekiguchi, Yuanzhong Li, and Yuichi Yamashita, presents a groundbreaking AI-driven method to enhance the randomization process in Alzheimer's disease clinical trials, significantly reducing participant allocation bias and trial size. Discover how they utilized a multimodal deep learning model to predict cognitive decline accurately!

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Citation Metrics
Citations
11
Influential Citations
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Reference Count
45
Citation by Year

Note: The citation metrics presented here have been sourced from Semantic Scholar and OpenAlex.

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