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Comment on: Cytokines (IL1β, IL6, TNFα) and serum cortisol levels may not constitute reliable biomarkers to identify individuals with post-acute sequelae of COVID-19
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Innovationsmanagement im Krankenhaus : Eine Handlungsempfehlung zur Reflexion und Bewertung von digitalen Technologien in der stationären Akutpflege
Get PDFHerstellung tragender medizinischer Implantate mit additiven Fertigungsverfahren auf der Basis von Polymerkompositen
No full textLongitudinal evaluation of laboratory results and method precision in worldwide erythropoietin external quality assessments
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Demystifying XAI : Requirements for Understandable XAI Explanations
Get PDFThis paper establishes requirements for assessing the usability of Explainable Artificial Intelligence (XAI) methods, focusing on non-AI experts like healthcare professionals. Through a synthesis of literature and empirical findings, it emphasizes achieving optimal cognitive load, task performance, and task time in XAI explanations. Key components include tailoring explanations to user expertise, integrating domain knowledge, and using non-propositional representations for comprehension. The paper highlights the critical role of relevance, accuracy, and truthfulness in fostering user trust. Practical guidelines are provided for designing transparent and user-friendly XAI explanations, especially in high-stakes contexts like healthcare. Overall, the paper's primary contribution lies in delineating clear requirements for effective XAI explanations, facilitating human-AI collaboration across diverse domains