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生成型人工智能的介绍:对未来进行上下文化
Rajendra Singh1, Ji Yeon Kim2, Eric F Glassy3
1From the Department of Pathology, Summit Health, Woodland Park, New Jersey (Singh).
Archives of pathology & laboratory medicine
|December 4, 2024
概括
生成型人工智能 (GAI) 为病理学提供了重大潜力,但需要仔细管理风险和偏见. 了解GAI的发展和实施对于病理学家在诊断医学中发挥领导作用至关重要.
科学领域:
- 病理学 病理学 病理学
- 人工智能的人工智能
- 医疗信息学 医疗信息学
背景情况:
- 生成型人工智能 (GAI) 正在迅速发展,为医疗保健专业人员带来机遇和挑战.
- 病理学家面临的困难跟上GAI的进步,术语和技术方面.
- 了解GAI对于识别其潜在风险和对病理学实践的影响至关重要.
研究的目的:
- 为病理学家提供有关GAI开发,评估和实施的可访问信息.
- 突出GAI对实验室应用和临床实践的相关性.
主要方法:
- 最近的研究和评论的文献综述.
- 这些信息来源于PubMed和arXiv数据库.
主要成果:
- GAI为病理学家带来了许多潜在的好处.
- 临床使用GAI需要严格监督和持续改进.
- GAI的表现取决于数据质量和多样性,存在偏差传播的风险.
- 伦理考虑,包括患者隐私和自主权,对于负责任的GAI部署至关重要.
结论:
- 病理学家可以利用GAI来增强诊断医学.
- 解决伦理问题和管理数据质量对于成功的GAI集成至关重要.
- 持续的学习和适应是病理学家保持在该领域的领导地位的关键.
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