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糖尿病视网膜病变(DRD)研究的数据协调、标准化和协作:2024 年玛丽·泰勒·摩尔视觉倡议数据研讨会报告。

Data Harmonization, Standardization, and Collaboration for Diabetic Retinal Disease (DRD) Research: Report From the 2024 Mary Tyler Moore Vision Initiative Workshop on Data.

机构信息

Wisconsin Reading Center, University of Wisconsin, Madison, WI, USA.

Department of Ophthalmology, Harvard Medical School, Boston, MA, USA.

出版信息

Transl Vis Sci Technol. 2024 Oct 1;13(10):4. doi: 10.1167/tvst.13.10.4.

Abstract

The 2024 Mary Tyler Moore Vision Initiative (MTM Vision) Workshop on Data convened to discuss best practices and specific considerations for building a comprehensive, shareable MTM Vision data lake. The workshop aimed to accelerate the development of new indications, therapies, and regulatory pathways for diabetic retinal disease (DRD) by standardizing and harmonizing clinical data and ocular 'omics analyses. Standardization of data collection, the use of common data elements, and data interoperability were emphasized, alongside federated learning approaches to promote data sharing and collaboration while maintaining data privacy and security. The integration of molecular data with other multimodal data types was recognized as a promising strategy for leveraging machine learning and AI approaches to advancing therapeutics development and improving treatment outcomes for DRD patients. Partnerships with entities such as the National Eye Institute, part of the National Institutes of Health, foundations, and industry were deemed vital for the successful implementation of these initiatives.

摘要

2024 年玛丽·泰勒·摩尔视觉倡议(MTM Vision)数据研讨会召开,旨在讨论构建全面、可共享的 MTM Vision 数据湖的最佳实践和具体注意事项。该研讨会旨在通过标准化和协调临床数据和眼部“组学”分析,加速糖尿病视网膜病变(DRD)的新适应症、疗法和监管途径的发展。强调了数据收集的标准化、通用数据元素的使用和数据互操作性,以及联邦学习方法,以促进数据共享和协作,同时保持数据隐私和安全。将分子数据与其他多模态数据类型相结合被认为是利用机器学习和人工智能方法推进治疗药物开发和改善 DRD 患者治疗效果的有前途的策略。与美国国立卫生研究院的国家眼科研究所、基金会和行业等实体的合作被认为对这些计划的成功实施至关重要。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cf5c/11451832/cd8c7c6a4c77/tvst-13-10-4-f001.jpg

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