An overview and a roadmap for artificial intelligence in hematology and oncology
Research output: Contribution to journal › Review article › Contributed › peer-review
Contributors
Abstract
Background: 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. Methods: 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. Results: 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. Conclusion: 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.
Details
Original language | English |
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Pages (from-to) | 7997-8006 |
Number of pages | 10 |
Journal | Journal of cancer research and clinical oncology |
Volume | 149 |
Issue number | 10 |
Publication status | Published - Aug 2023 |
Peer-reviewed | Yes |
External IDs
PubMed | 36920563 |
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Keywords
Sustainable Development Goals
ASJC Scopus subject areas
Keywords
- Artificial intelligence, Computer vision, Digital health, Large language models, Machine learning, Medical Oncology, Hematology, Humans, Artificial Intelligence, Forecasting