人工智能和机器学习在辅助生殖技术中的作用
Victoria S Jiang1, Zoran J Pavlovic2, Eduardo Hariton3
1Division of Reproductive Endocrinology & Infertility, Vincent Department of Obstetrics and Gynecology, Massachusetts General Hospital/Harvard Medical School, 55 Fruit Street, Suite 10A, Boston, MA 02116, USA.
Obstetrics and gynecology clinics of North America
|November 1, 2023
概括
人工智能 (AI) 和机器学习可以通过改善诊断和患者护理来增强生殖医学. 然而,理解人工智能是很难的.
科学领域:
- 生殖医学 生殖医学
- 医疗保健中的人工智能
- 机器学习应用 机器学习应用
背景情况:
- 人工智能 (AI) 和机器学习 (ML) 利用大数据集和算法来实现医学进步.
- 这些技术在治疗,医疗保健和患者治疗结果方面具有变革性的潜力.
- 生殖医学将从人工智能驱动的创新中受益显著.
研究的目的:
- 探索人工智能在生殖医学中的能力和局限性.
- 突出AI在个性化患者护理和改善结果方面的潜力.
- 解决医疗保健中人工智能算法固有的偏见和歧视风险.
主要方法:
- 利用大型数据集和智能算法进行医学分析.
- 为特定的生殖健康应用开发和应用机器学习模型.
- 分析AI对临床决策和患者护理途径的影响.
主要成果:
- 人工智能可以增强卵细胞和胚胎分类,并提高卵泡测量精度.
- 人工智能促进了个性化的患者护理,并优化了治疗策略.
- 人工智能有可能彻底改变获得和提供生殖保健服务的机会.
结论:
- 人工智能为推进生殖医学和改善家庭建设结果提供了重大前景.
- 意识到人工智能的局限性,包括易受社会经济和人口偏见的影响,至关重要.
- 对人工智能的明智应用对于防止错误诊断和医疗保健歧视至关重要,确保公平的利益.
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