Gaffney Harry, Mirza Kamran M
Concord Clinical School, Faculty of Medicine and Health, The University of Sydney, Sydney, New South Wales, Australia.
The Godfrey D. Stobbe Professor of Pathology Education, Assistant Chair for Education and Director of the Division of Training, Programs and Communication, University of Michigan (Michigan Medicine) Department of Pathology, Ann Arbor, MI, USA.
Acad Pathol. 2025 Feb 28;12(1):100166. doi: 10.1016/j.acpath.2025.100166. eCollection 2025 Jan-Mar.
The integration of artificial intelligence in pathology has ignited discussions about the role of technology in diagnostics-whether artificial intelligence serves as a tool for augmentation or risks replacing human expertise. This manuscript explores artificial intelligence's evolving contributions to pathology, emphasizing its potential capacity to enhance, rather than eclipse, the pathologist's role. Through historical comparisons, such as the transition from analog to digital in radiology, this paper highlights how technological advancements have historically expanded professional capabilities without diminishing the essential human element. Current applications of artificial intelligence in pathology-from diagnostic standardization to workflow efficiency-demonstrate its potential to augment diagnostic accuracy, expedite processes, and improve consistency across institutions. However, challenges remain in algorithmic bias, regulatory oversight, and maintaining interpretive skills among pathologists. The discussion underscores the importance of comprehensive governance frameworks, evolving educational curricula, and public engagement initiatives to ensure artificial intelligence in pathology remains a collaborative endeavor that empowers professionals, upholds ethical standards, and enhances patient outcomes. This manuscript ultimately advocates for a balanced approach where artificial intelligence and human expertise work in concert to advance the future of diagnostic medicine.
人工智能在病理学中的整合引发了关于技术在诊断中作用的讨论——人工智能究竟是作为一种辅助工具,还是存在取代人类专业知识的风险。本文探讨了人工智能对病理学不断演变的贡献,强调其增强病理学家作用的潜在能力,而非使其黯然失色。通过历史比较,如放射学从模拟到数字的转变,本文强调了技术进步如何在不削弱关键人为因素的情况下,从历史上拓展专业能力。人工智能在病理学中的当前应用——从诊断标准化到工作流程效率——展示了其提高诊断准确性、加快流程以及改善各机构间一致性的潜力。然而,在算法偏差、监管监督以及病理学家保持解释技能方面仍存在挑战。讨论强调了全面治理框架、不断发展的教育课程以及公众参与倡议的重要性,以确保病理学中的人工智能仍然是一项协作性努力,能够赋予专业人员权力、维护道德标准并改善患者治疗结果。本文最终倡导一种平衡的方法,即人工智能和人类专业知识协同工作,以推动诊断医学的未来发展。