The results have shown that appropriately designed EIs may improve the anesthetist's decision making and focus attention on specific problems. Now, the findings have to be tested in future studies by widening the scope using other simulated scenarios and being closer to reality under real conditions in the OR. Eye tracking proved to be a useful method to analyze the anesthetists' decision making and appropriately re-design interfaces.
Our results have shown that subjects came to more effective solutions with the traditional trend display. The main reason for this result may be their years of experience with this kind of display type. Regarding safe and goal-intended decision finding, the results are encouraging for further experiments with redesigned ecological displays. But these displays ought to have smoother changes with respect to the traditional trend displays. Furthermore, new experiments have to be performed under real or fairly real (e.g. together with an anaesthesia simulator) conditions to underline the positive results for ecological interfaces.
Machine intelligence, a.k.a. artificial intelligence (AI) is one of the most prominent and relevant technologies today. It is in everyday use in the form of AI applications and has a strong impact on society. This article presents selected results of the 2020 Dagstuhl workshop on applied machine intelligence. Selected AI applications in various domains, namely culture, education, and industrial manufacturing are presented. Current trends, best practices, and recommendations regarding AI methodology and technology are explained. The focus is on ontologies (knowledge-based AI) and machine learning.
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