人工智能 (AI) 的路线图:设计和构建AI准备数据的方法 妇女健康研究 数据
Farah Kidwai-Khan1,2, Rixin Wang1,2, Melissa Skanderson2
1Yale School of Medicine, New Haven, Connecticut, USA.
medRxiv : the preprint server for health sciences
|July 3, 2023
概括
开发有效的数据框架对于将人工智能 (AI) 应用于妇女健康研究至关重要. 优化数据准备将算法偏差降至最低,并提高了跌倒和骨折的预测能力.
科学领域:
- 医疗信息学 医疗信息学
- 人工智能在医学中的应用
- 数据科学数据科学数据科学
背景情况:
- 妇女健康研究中的大型数据集需要强大的数据框架来进行先进的分析.
- 应用机器学习 (ML) 和自然语言处理 (NLP) 需要优化数据准备以减轻算法偏差.
结论:
- 数据生命周期,从原始到分析形式,涉及到治理,清洁,管理和分析.
- 优化数据准备对于减少人工智能研究中的算法偏差至关重要.
- 准备好的人工智能数据框架对于提高女性健康研究的效率和减少偏见至关重要.
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