Fabian Berns, Niclas Heilig, Florian Stumpe, Jan Kirchhoff
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Medical operational AI: artificial intelligence in routine medical operations
Abstract Despite substantial gains facilitated by Artificial Intelligence (AI) in recent years, it has to be applied very cautiously in sensitive domains like medicine due to the lack of explainability of many methods in this field. We aim to provide a system to overcome these issues of medical AI applications by means of our concept of medical operational AI detailed in this paper. We make use of various methods of AI and utilize knowledge graphs in particular. The latter is continuously updated by medical experts based on medical literature such as peer-reviewed papers and standard online sources such as UpToDate. We thoroughly derive a multi-level system tackling the corresponding challenges. In particular, its design encompasses (i) holistic diagnostic assistance on a macro level, (ii) predicitions and detailed suggestions for specific medical domains on a micro level, as well as (iii) AI-based optimizations of the overall system on a meta level. We detail practical merits of medical operational AI and discuss the state of the art beyond our solution.
期刊介绍:
The Journal of Laboratory Medicine (JLM) is a bi-monthly published journal that reports on the latest developments in laboratory medicine. Particular focus is placed on the diagnostic aspects of the clinical laboratory, although technical, regulatory, and educational topics are equally covered. The Journal specializes in the publication of high-standard, competent and timely review articles on clinical, methodological and pathogenic aspects of modern laboratory diagnostics. These reviews are critically reviewed by expert reviewers and JLM’s Associate Editors who are specialists in the various subdisciplines of laboratory medicine. In addition, JLM publishes original research articles, case reports, point/counterpoint articles and letters to the editor, all of which are peer reviewed by at least two experts in the field.