AI-READI: rethinking AI data collection, preparation and sharing in diabetes research and beyond

IF 5.1 Q1 POLYMER SCIENCE ACS Macro Letters Pub Date : 2024-11-08 DOI:10.1038/s42255-024-01165-x
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Abstract

Here, we introduce Artificial Intelligence Ready and Equitable Atlas for Diabetes Insights (AI-READI), a multidisciplinary data-generation project designed to create and share a multimodal dataset optimized for artificial intelligence research in type 2 diabetes mellitus.

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AI-READI:重新思考糖尿病研究及其他领域的人工智能数据收集、准备和共享问题
在此,我们介绍人工智能糖尿病洞察力公平图集(AI-READI),这是一个多学科数据生成项目,旨在创建和共享一个多模态数据集,该数据集经过优化,可用于 2 型糖尿病的人工智能研究。
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来源期刊
CiteScore
10.40
自引率
3.40%
发文量
209
审稿时长
1 months
期刊介绍: ACS Macro Letters publishes research in all areas of contemporary soft matter science in which macromolecules play a key role, including nanotechnology, self-assembly, supramolecular chemistry, biomaterials, energy generation and storage, and renewable/sustainable materials. Submissions to ACS Macro Letters should justify clearly the rapid disclosure of the key elements of the study. The scope of the journal includes high-impact research of broad interest in all areas of polymer science and engineering, including cross-disciplinary research that interfaces with polymer science. With the launch of ACS Macro Letters, all Communications that were formerly published in Macromolecules and Biomacromolecules will be published as Letters in ACS Macro Letters.
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