Department for Medical Oncology and Hematology, University Hospital Zurich, Zurich, Switzerland.
Department of Medical Bioinformatics, University Medical Center Göttingen, Göttingen, Germany.
J Cancer Res Clin Oncol. 2023 Aug;149(10):7997-8006. doi: 10.1007/s00432-023-04667-5. Epub 2023 Mar 15.
Artificial intelligence (AI) is influencing our society on many levels and has broad implications for the future practice of hematology and oncology. However, for many medical professionals and researchers, it often remains unclear what AI can and cannot do, and what are promising areas for a sensible application of AI in hematology and oncology. Finally, the limits and perils of using AI in oncology are not obvious to many healthcare professionals.
In this article, we provide an expert-based consensus statement by the joint Working Group on "Artificial Intelligence in Hematology and Oncology" by the German Society of Hematology and Oncology (DGHO), the German Association for Medical Informatics, Biometry and Epidemiology (GMDS), and the Special Interest Group Digital Health of the German Informatics Society (GI). We provide a conceptual framework for AI in hematology and oncology.
First, we propose a technological definition, which we deliberately set in a narrow frame to mainly include the technical developments of the last ten years. Second, we present a taxonomy of clinically relevant AI systems, structured according to the type of clinical data they are used to analyze. Third, we show an overview of potential applications, including clinical, research, and educational environments with a focus on hematology and oncology.
Thus, this article provides a point of reference for hematologists and oncologists, and at the same time sets forth a framework for the further development and clinical deployment of AI in hematology and oncology in the future.
人工智能(AI)正在多个层面上影响我们的社会,并对血液病学和肿瘤学的未来实践产生广泛影响。然而,对于许多医学专业人员和研究人员来说,他们往往不清楚 AI 能做什么、不能做什么,以及在血液病学和肿瘤学中合理应用 AI 的有哪些有前景的领域。最后,许多医疗保健专业人员并不清楚在肿瘤学中使用 AI 的局限性和危险。
在本文中,我们提供了由德国血液学和肿瘤学学会(DGHO)、德国医学信息学、生物统计学和流行病学协会(GMDS)以及德国信息学学会数字健康专业组(GI)的联合“血液学和肿瘤学人工智能”工作组提供的基于专家的共识声明。我们为血液学和肿瘤学中的 AI 提供了一个概念框架。
首先,我们提出了一个技术定义,我们故意将其设置在一个狭窄的框架内,主要包括过去十年的技术发展。其次,我们提出了一种临床相关 AI 系统的分类法,根据它们用于分析的临床数据类型进行结构化。第三,我们展示了潜在应用的概述,包括临床、研究和教育环境,重点是血液病学和肿瘤学。
因此,本文为血液学家和肿瘤学家提供了一个参考点,同时为未来在血液病学和肿瘤学中进一步开发和临床部署 AI 提供了一个框架。