[希波克拉底与语言模式--primum non nocere --首先,不要伤害]。

Harefuah Pub Date : 2024-11-01
Sharon Einav, Or Degany, Yehuda Shoenfeld
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引用次数: 0

摘要

导言:千百年来,希波克拉底提出的 "首先,不伤害 "精神一直是医学的基石。这一原则强调了临床医生对病人利益的责任和道德承诺。近来,人工智能(AI)的快速发展正在改变医学世界,不仅对诊断、治疗方案、研究、医学教育和医学伦理产生重大影响,也影响着我们的思维方式。为了最大限度地发挥人工智能的优势,了解其局限性,防止对患者造成潜在伤害,临床医生应该了解人工智能的基本原理。这种熟悉将使临床医生能够正确评估人工智能工具生成的输出结果;从有针对性的系统提出的医疗建议(如用于解释胸部放射成像的决策支持系统),到非特定人工智能工具(如大型语言模型)提出的诊断和治疗方案。计算能力、算法和数据存储的发展使人工智能领域取得了重大进展,包括生成式人工智能的出现。本综述将医学研究的基本概念与人工智能发展的各个阶段联系起来,包括神经网络和深度学习原理。它提供了一个常用人工智能术语表,并对大型语言模型的开发和运作提供了深入见解。报告还讨论了人工智能对医患关系的潜在影响。报告还提出了几项可操作的建议,这些建议可以改善人工智能与临床工作的结合,同时又能保持基本的伦理原则,即有利、无弊、公正和自主。其中包括适当的模型培训、监管以及医疗界参与这些模型的开发并将其融入临床实践。这种参与将确保医学伦理原则始终处于最前沿,不会因开发实体的利益而受到损害。信息披露:Sharon Einav 教授和 Or Degany 受雇于 Medint Medical Intelligence 公司。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
[HIPPOCRATES AND LANGUAGE MODELS - PRIMUM NON NOCERE - FIRST, DO NO HARM].

Introduction: For millennia, the ethos of "First, Do No Harm", attributed to Hippocrates, has been a cornerstone of medicine. This principle emphasizes the responsibility and ethical commitment of the clinician to the benefit of their patient. Recently, the rapid development of artificial intelligence (AI) is transforming the medical world, significantly affecting not only diagnosis, treatment plans, research, medical education, and medical ethics, but also the way we think. To maximize the benefits of AI, understand its limitations, and prevent potential harm to patients, clinicians should be aware of the principles underlying artificial intelligence. Such familiarity will enable the clinician to correctly assess outputs generated by AI tools; from medical recommendations proposed by targeted systems (such as a decision-support system for the interpretation of chest radiography) to diagnoses and treatment plans proposed by non-specific AI tools such as large language models. Developments in computing power, algorithms, and data storage have enabled significant progress in the world of AI, including the emergence of generative AI. This review bridges fundamental medical research concepts with stages of AI development, encompassing neural networks, and deep learning principles. It offers a glossary of commonly used AI terms and provides insights into the development and functioning of large language models. The potential influence of AI on the patient-physician relationship is also discussed. Several proposals are presented for actionable items that may improve the integration of AI into clinical work while maintaining the basic ethical principles of beneficence, non-maleficence, justice, and autonomy. They include proper model training, regulation, and involvement of the medical community in the development and integration of these models into clinical practice. Such involvement will ensure that the ethical principles of medicine remain at the forefront, and are not compromised by the interests of the developing entities. Disclosures: Prof. Sharon Einav and Or Degany are employed by Medint Medical Intelligence.

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