Innovating Challenges and Experiences in Emory Health AI Bias Datathon: Experience Report.

Atika Rahman Paddo, Saptarshi Purkayastha, Janice Newsome, Hari Trivedi, Judy Wawira Gichoya
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引用次数: 0

Abstract

This paper presents an in-depth analysis of the Emory Health AI (Artificial Intelligence) Bias Datathon held in August 2023, providing insights into the experiences gained during the event. The datathon, focusing on health-related issues, attracted diverse participants, including professionals, researchers, and students from various backgrounds. The paper discusses the preparation, organization, and execution of the datathon, detailing the registration process, team formulation, dataset creation, and logistical aspects. We also explore the achievements and personal experiences of participants, highlighting their resilience, dedication, and innovative contributions. The findings include a breakdown of participant demographics, responses to post-event surveys, and participant backgrounds. Observing the trends, we believe the lessons learned, and the overall impact of the Emory Health AI Bias Datathon on the participants and the field of health data science will contribute significantly in organizing future datathons.

埃默里健康人工智能偏见数据马拉松的创新挑战和经验:经验报告。
本文对2023年8月举行的埃默里健康AI(人工智能)偏见数据马拉松进行了深入分析,并提供了在活动期间获得的经验见解。数据马拉松关注与健康有关的问题,吸引了各种各样的参与者,包括来自不同背景的专业人士、研究人员和学生。本文讨论了数据马拉松的准备、组织和执行,详细介绍了注册过程、团队组建、数据集创建和后勤方面。我们还探讨了参与者的成就和个人经历,突出了他们的韧性、奉献精神和创新贡献。调查结果包括参与者的人口统计数据、对事后调查的回应以及参与者的背景。观察这些趋势,我们相信从中吸取的教训,以及埃默里健康人工智能偏见数据马拉松对参与者和健康数据科学领域的整体影响,将为组织未来的数据马拉松做出重大贡献。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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