El-Khoury Riyad, Zaatari Ghazi
Department of Pathology and Laboratory Medicine, American University of Beirut Medical Center, Beirut 1107 2020, Lebanon.
Diagnostics (Basel). 2025 Sep 11;15(18):2308. doi: 10.3390/diagnostics15182308.
Over 150 years, pathology has transformed remarkably, from the humble beginnings of microscopic tissue examination to today's revolutionary advancements in digital pathology and artificial intelligence (AI) applications. This review briefly retraces the evolution of microscopes and highlights breakthroughs in complementary tools and techniques that laid the foundation for modern surgical pathology, recently expanded into a new dimension with digital pathology. Digital pathology marked a pivotal turning point by addressing the longstanding limitations of conventional microscopy, paving the way for AI integration. AI now revolutionizes pathology workflows, offering unprecedented opportunities for automated diagnostics, enhanced precision, accelerated research, and advanced medical education. Despite widespread consensus on AI as complementary to pathologists, rare studies critically explore the feasibility of a fully autonomous, pathologist-independent diagnostic workflow. Given the rapid advancement of AI, it is timely to examine whether mature AI systems might realistically achieve diagnostic autonomy. Thus, this review uniquely addresses this gap by evaluating the feasibility, limitations, and implications of a disruptive, pathologist-free diagnostic model. This exploration raises critical questions about the evolving role of pathologists in an era increasingly defined by automation. Can pathologists adapt to emerging trends, maintain their central role in patient care, and leverage AI effectively, or will their traditional roles inevitably diminish? Could the continued advancement of AI eventually prompt a return of pathologists to their initial mid-19th century role as scientist scholars, removed from frontline diagnostics? Ultimately, we assess whether AI can independently sustain diagnostic accuracy and decision making without pathologist oversight.
在过去的150多年里,病理学发生了显著的变革,从微观组织检查的 humble beginnings 发展到如今数字病理学和人工智能(AI)应用方面的革命性进展。本综述简要回顾了显微镜的发展历程,并突出了为现代外科病理学奠定基础的互补工具和技术方面的突破,最近数字病理学又将其扩展到了一个新的维度。数字病理学通过解决传统显微镜长期存在的局限性,标志着一个关键的转折点,为人工智能的整合铺平了道路。人工智能如今正在彻底改变病理学工作流程,为自动化诊断、提高精度、加速研究和推进医学教育提供了前所未有的机会。尽管人们普遍认为人工智能是病理学家的辅助工具,但很少有研究批判性地探讨完全自主、无需病理学家的诊断工作流程的可行性。鉴于人工智能的快速发展,现在是时候审视成熟的人工智能系统是否真的能够实现诊断自主性了。因此,本综述通过评估一种颠覆性的、无需病理学家的诊断模型的可行性、局限性和影响,独特地填补了这一空白。这次探索引发了关于病理学家在一个日益由自动化定义的时代中不断演变的角色的关键问题。病理学家能否适应新趋势,在患者护理中保持核心地位,并有效地利用人工智能,还是他们的传统角色将不可避免地减少?人工智能的持续进步最终是否会促使病理学家回归到19世纪中叶作为科学家学者的最初角色,远离一线诊断?最终,我们评估人工智能在没有病理学家监督的情况下能否独立维持诊断准确性和决策。