通过自然语言处理和聊天机器人技术彻底改变细胞学和细胞病理学:关于当前趋势和未来方向的叙述性审查
Andrea Lastrucci1, Enrico Giarnieri2, Elisabetta Carico2
1Department of Allied Health Professions, Azienda Ospedaliero-Universitaria Careggi, 50134 Florence, Italy.
Bioengineering (Basel, Switzerland)
|November 27, 2024
概括
聊天机器人和自然语言处理 (NLP) 显示出改善细胞学中的医学诊断的希望. 需要进一步的研究来应对数据标准化和人工智能偏见等挑战,以实现负责任的实施.
科学领域:
- 医学诊断 医学诊断 医学诊断
- 计算病理学计算病理学
- 医疗保健中的人工智能
背景情况:
- 聊天机器人和自然语言处理 (NLP) 在细胞学和细胞病理学中的集成是一个新兴的研究领域.
- 目前的文献有限,但越来越多,表明这些技术在医学诊断中的巨大潜力.
研究的目的:
- 对聊天机器人和NLP在细胞学和细胞病理学方面的早期发展和未来影响进行叙事审查.
- 探索与在诊断工作流程中实施这些AI技术相关的机遇和挑战.
主要方法:
- 采用了一个叙事审查方法.
- 标准化检查清单和质量控制程序用于科学论文的纳入.
- 在排除非研究文章后,分析了11项相关研究.
主要成果:
- 聊天机器人和NLP提供了提高诊断准确度,简化工作流程和改善患者在细胞学中的参与的机会.
- 这些技术可以自动提取和分类医疗信息,减少错误并提高精度.
- 潜在的好处包括改善患者获取信息的机会和加强决策过程.
结论:
- 聊天机器人和NLP在细胞学和细胞病理学方面具有变革性的潜力,尽管目前存在挑战.
- 未来发展的关键领域包括数据标准化,AI偏差缓解,临床验证和解决伦理/法律方面的考虑.
- 利用放射学等相关领域的进步可以加速这些数字工具的整合.
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