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数字病理学在癌症诊断中的应用:迈向明智决策

Digital pathology implementation in cancer diagnostics: towards informed decision-making.

作者信息

Sulaieva Oksana, Dudin Oleksandr, Koshyk Olena, Panko Mariia, Kobyliak Nazarii

机构信息

Medical Laboratory CSD, Kyiv, Ukraine.

Endocrinology Department, Bogomolets National Medical University, Kyiv, Ukraine.

出版信息

Front Digit Health. 2024 May 30;6:1358305. doi: 10.3389/fdgth.2024.1358305. eCollection 2024.

DOI:10.3389/fdgth.2024.1358305
PMID:38873358
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11169727/
Abstract

Digital pathology (DP) has become a part of the cancer healthcare system, creating additional value for cancer patients. DP implementation in clinical practice provides plenty of benefits but also harbors hidden ethical challenges affecting physician-patient relationships. This paper addresses the ethical obligation to transform the physician-patient relationship for informed and responsible decision-making when using artificial intelligence (AI)-based tools for cancer diagnostics. DP application allows to improve the performance of the Human-AI Team shifting focus from AI challenges towards the Augmented Human Intelligence (AHI) benefits. AHI enhances analytical sensitivity and empowers pathologists to deliver accurate diagnoses and assess predictive biomarkers for further personalized treatment of cancer patients. At the same time, patients' right to know about using AI tools, their accuracy, strengths and limitations, measures for privacy protection, acceptance of privacy concerns and legal protection defines the duty of physicians to provide the relevant information about AHI-based solutions to patients and the community for building transparency, understanding and trust, respecting patients' autonomy and empowering informed decision-making in oncology.

摘要

数字病理学(DP)已成为癌症医疗体系的一部分,为癌症患者创造了额外价值。在临床实践中实施DP有诸多益处,但也潜藏着影响医患关系的隐性伦理挑战。本文探讨了在使用基于人工智能(AI)的工具进行癌症诊断时,为实现知情且负责的决策而转变医患关系的伦理义务。DP的应用有助于提升人机智能团队的效能,将关注点从AI的挑战转向增强人类智能(AHI)的益处。AHI提高了分析敏感性,使病理学家能够做出准确诊断,并评估预测性生物标志物,以便为癌症患者提供进一步的个性化治疗。与此同时,患者有权了解AI工具的使用情况、其准确性、优势和局限性、隐私保护措施、对隐私问题的接受程度以及法律保护,这界定了医生有责任向患者和社会提供有关基于AHI的解决方案的相关信息,以建立透明度、增进理解与信任,尊重患者的自主权,并促进肿瘤学领域的知情决策。

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Digital Pathology: Transforming Diagnosis in the Digital Age.数字病理学:变革数字时代的诊断方式。
Cureus. 2023 Sep 3;15(9):e44620. doi: 10.7759/cureus.44620. eCollection 2023 Sep.
2
Comparison of Mammography AI Algorithms with a Clinical Risk Model for 5-year Breast Cancer Risk Prediction: An Observational Study.对比钼靶 X 线摄影人工智能算法与临床风险模型预测 5 年乳腺癌风险:一项观察性研究。
Radiology. 2023 Jun;307(5):e222733. doi: 10.1148/radiol.222733.
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Learning at a distance: results of an international survey on the adoption of virtual conferences and whole slide imaging by pathologists.远程学习:病理学家采用虚拟会议和全玻片成像技术的国际调查结果。
J Clin Pathol. 2024 Aug 16;77(9):632-638. doi: 10.1136/jcp-2023-208912.
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Privacy risks of whole-slide image sharing in digital pathology.数字病理学中全切片图像共享的隐私风险。
Nat Commun. 2023 May 4;14(1):2577. doi: 10.1038/s41467-023-37991-y.
5
Ethical and legal considerations influencing human involvement in the implementation of artificial intelligence in a clinical pathway: A multi-stakeholder perspective.影响人类参与临床路径中人工智能实施的伦理和法律考量:多利益相关方视角
Front Digit Health. 2023 Mar 13;5:1139210. doi: 10.3389/fdgth.2023.1139210. eCollection 2023.
6
Ethics and governance of trustworthy medical artificial intelligence.可信医疗人工智能的伦理与治理。
BMC Med Inform Decis Mak. 2023 Jan 13;23(1):7. doi: 10.1186/s12911-023-02103-9.
7
The key to an effective AI-powered digital pathology: Establishing a symbiotic workflow between pathologists and machine.有效利用人工智能的数字病理学的关键:在病理学家和机器之间建立共生工作流程。
J Pathol Inform. 2022 Nov 10;13:100156. doi: 10.1016/j.jpi.2022.100156. eCollection 2022.
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The dark sides of AI.人工智能的阴暗面。
Electron Mark. 2022;32(1):11-15. doi: 10.1007/s12525-022-00531-5. Epub 2022 Feb 22.
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The medical algorithmic audit.医学算法审计
Lancet Digit Health. 2022 May;4(5):e384-e397. doi: 10.1016/S2589-7500(22)00003-6. Epub 2022 Apr 5.
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