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文献精选 > 高引权威"AI药物发现"文献

AI in health and medicine. ​

文献信息 ​

DOI10.1038/s41591-021-01614-0
PMID35058619
期刊Nature medicine
影响因子50.0
JCR 分区Q1
发表年份2022
被引次数723
关键词人工智能, 医学影像分析, 人机协作, 技术挑战, 伦理问题
文献类型Journal Article, Research Support, N.I.H., Extramural, Review
ISSN1078-8956
页码31-38
期号28(1)
作者Pranav Rajpurkar, Emma Chen, Oishi Banerjee, Eric J Topol

一句话小结 ​

该研究总结了为期两年的医疗人工智能进展，强调了前瞻性研究和医疗图像分析在缩小研究与应用差距方面的重要性，同时探讨了新兴研究方向及面临的技术和伦理挑战。研究表明，解决这些挑战将有助于实现AI在医学中的潜力，从而提升全球患者的医疗服务质量和可及性。

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人工智能 · 医学影像分析 · 人机协作 · 技术挑战 · 伦理问题

摘要 ​

人工智能（AI）有望广泛重塑医学，可能改善临床医生和患者的体验。我们讨论了为期两年的每周努力所获得的关键发现，旨在追踪和分享医疗AI的主要进展。我们涵盖了前瞻性研究和医疗图像分析的进展，这些进展缩小了研究与应用之间的差距。我们还探讨了几条有前景的新型医疗AI研究方向，包括非图像数据来源、非常规问题表述和人机协作。最后，我们考虑了一些严重的技术和伦理挑战，这些问题涉及数据稀缺到种族偏见等多个方面。随着这些挑战的解决，AI的潜力可能得以实现，使全球患者的医疗服务更加精准、高效和可及。

英文摘要 ​

Artificial intelligence (AI) is poised to broadly reshape medicine, potentially improving the experiences of both clinicians and patients. We discuss key findings from a 2-year weekly effort to track and share key developments in medical AI. We cover prospective studies and advances in medical image analysis, which have reduced the gap between research and deployment. We also address several promising avenues for novel medical AI research, including non-image data sources, unconventional problem formulations and human-AI collaboration. Finally, we consider serious technical and ethical challenges in issues spanning from data scarcity to racial bias. As these challenges are addressed, AI's potential may be realized, making healthcare more accurate, efficient and accessible for patients worldwide.

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主要研究问题 ​

  1. 在医疗AI的发展中，非图像数据源如何被有效利用以提升诊断准确性？
  2. 人工智能在医疗领域中的伦理挑战有哪些，如何确保技术的公平性与透明度？
  3. AI与医生之间的协作模式如何演变，以改善患者的治疗体验？
  4. 目前在医疗AI研究中，存在哪些主要的技术障碍，未来的解决方案可能是什么？
  5. 如何评估医疗AI技术在不同人群中的适用性，以避免种族偏见和数据稀缺问题？

核心洞察 ​

1. 研究背景和目的 ​

随着人工智能（AI）技术的迅速发展，它在医疗领域的应用正日益受到关注。研究旨在追踪和分享医疗AI的关键进展，特别是如何通过技术进步提升临床医生和患者的体验。此项研究为期两年，聚焦于医疗影像分析的前瞻性研究及其从研究到实际应用的转化。

2. 主要方法和发现 ​

研究采用了定期跟踪的方法，每周汇总医疗AI领域的最新进展。重点讨论了医疗影像分析的进展，强调这些技术在缩小研究与实际应用之间的差距方面所发挥的作用。此外，研究还探讨了其他潜在的医疗AI研究方向，包括非影像数据来源、非传统问题的解决方案以及人机协作的模式。这些研究发现表明，AI在医疗领域的应用具有广泛的可能性和潜力。

3. 核心结论 ​

AI在医疗健康领域的应用能够显著提高医疗服务的准确性、效率和可及性。然而，研究同时指出，技术和伦理方面的一些挑战仍需认真对待，包括数据稀缺性和种族偏见等问题。随着这些挑战的逐步解决，AI的潜力将得以充分发挥，从而改善全球患者的医疗体验。

4. 研究意义和影响 ​

本研究的重要性在于它提供了医疗AI领域的全面视角，强调了技术进步带来的积极变化及其在医疗实践中的实际应用。通过系统地跟踪和分析医疗AI的进展，研究为未来医疗AI研究提供了方向，推动了医护人员与AI的协作模式。同时，该研究也提醒业界在追求技术创新的同时，必须关注伦理和社会责任，以确保AI技术的公平和有效应用。这一研究成果不仅为医疗行业提供了宝贵的数据支持，也为政策制定者和研究者在医疗AI的未来发展中提供了有力的参考依据。

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