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野村综合研究所(NRI):2024生成式AI在医疗保健领域的变革潜力研究报告:提升诊断与运营(中译版)(16页).pdf

上传人: Kell****reet 编号:188277 2024-12-31 16页 2.30MB

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1、Generative AIs Potential Generative AIs Potential to Reshape Healthcareto Reshape HealthcareStrategic Design and Digital Transformation,NRI India 2Executive SummaryChallenges Faced by the Healthcare IndustryThe use of AI in healthcare has grown significantly,offering transformativ potential in areas

2、 ranging from diagnostics and imaging to drug discovery and personalized treatment.Advanced algorithms can now diagnose diseases quickly and accurately,often with a precision that rivals human experts,while streamlining drug development and tailoring treatments to individual patient profiles.Despite

3、 these innovations,the healthcare industry faces significant challenges,including a severe shortage of healthcare professionals and inefficient systems,leading to rising costs for payers.The introduction of Generative AI could usher in a new era of personalized medicine and operational efficiency in

4、 healthcare.By harnessing its ability to generate novel data,it can assist in the development of patient-specific medical solutions,from automated medical notes and diagnosis to the generation of tailored drug combinations.But it also requires rigorous validation to ensure safety and efficacy,presen

5、ting both exciting potential and challenges for the industry.Administrative error puts lives at risk:There is a 1 in 300 chance that an individual will suffer harm during their healthcare journey.Previous studies have shown that up to 50%of medical errors in primary care are due to administrative ov

6、ersight.Such errors can have far-reaching consequences,including failure to detect critical conditions or misdiagnosis.This can lead to inappropriate treatment and inappropriate scheduling of necessary interventions.The high prevalence of 2024 Nomura Research Institute,Ltd.All Rights Reserved.3these

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本文主要探讨了生成性AI在医疗保健领域的潜力与挑战。生成性AI能够通过学习现有数据生成新的内容,如文本、图像、视频或音乐,对医疗保健行业产生重大影响。 1. 医疗保健行业面临的挑战包括医疗专业人员短缺、效率低下和成本上升。 2. 生成性AI的引入有望开启个性化医疗和运营效率的新时代。 3. 生成性AI在医疗保健领域的应用包括知识管理、AI驱动的病理学、个性化治疗计划、自动化索赔审查和编辑等。 4. 生成性AI在医疗保健领域的风险包括固有偏见、幻觉、缺乏透明度和数据隐私问题。 5. 为了利用生成性AI的力量,医疗保健组织应制定战略,包括形成跨职能团队、投资于强大的数据管理工具、聘请内部AI专家并提供持续培训。
医疗AI如何改变个性化医疗? 生成式AI在药物研发中的应用有哪些? 医疗AI的偏见风险有哪些?
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