黑色素瘤诊断中的人工智能:三种情况、能力的转变、监管的必要性以及调和人类与人工智能之间的分歧

Jan C. Zoellick, Hans Drexler, Konstantin Drexler
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引用次数: 0

摘要

越来越多基于机器学习(即所谓的人工智能)的工具被开发出来,用于皮肤科恶性黑色素瘤的诊断。本文将讨论:(1) 在不同医疗环境中使用人工智能的三种情况;(2) 能力从皮肤科医生向非专科医生和获得授权的患者的转移;(3) 确保安全和有效性的监管框架及其对人工智能工具的影响;(4) 认知失调和将人类决策权委托给人工智能的可能性。我们的结论是,人工智能系统不应取代人类的医疗专业知识,而应发挥辅助作用。我们确定了监管需求,并提出了行动建议,以帮助所有(人类)参与者在这一新兴市场的波涛汹涌中安全航行。当人工智能工具提供的诊断结果与人类医学专业知识相冲突时,就会出现潜在的困境。调和这些冲突将是一项重大挑战。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Artificial intelligence in melanoma diagnosis: Three scenarios, shifts in competencies, need for regulation, and reconciling dissent between humans and AI
Tools based on machine learning (so-called artificial intelligence, AI) are increasingly being developed to diagnose malignant melanoma in dermatology. This contribution discusses (1) three scenarios for the use of AI in different medical settings, (2) shifts in competencies from dermatologists to non-specialists and empowered patients, (3) regulatory frameworks to ensure safety and effectiveness and their consequences for AI tools, and (4) cognitive dissonance and potential delegation of human decision-making to AI. We conclude that AI systems should not replace human medical expertise but play a supporting role. We identify needs for regulation and provide recommendations for action to help all (human) actors navigate safely through the choppy waters of this emerging market. Potential dilemmas arise when AI tools provide diagnoses that conflict with human medical expertise. Reconciling these conflicts will be a major challenge.
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