ReviewAdvances in experimental medicine and biology2021
Expert Characteristics: Implications for Expert Systems.
Review in Advances in experimental medicine and biology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
0 citing papers in PubMed.
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Authors and funding
1 author.
Funding
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Abstract
While expert systems are artificial intelligence (AI) agents, they share many common characteristics with human experts. As technology progresses, such systems are not just able to make simple decisions following "simplistic" linear logical protocols; they "behave" as real experts in at least two ways: by demonstrating superb decision-making skills and by conforming to the social norms for expertise, i.e., they "feel" as human experts. A review of the common characteristics of human experts may have important implications for the direction of the development for such systems. Implications for bioinformatics and future research (especially concerning the accompanying concept of "expert generalist") are also discussed.
Indexed as
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34973020What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.