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BioASQ Synergy: a dialogue between question-answering systems and biomedical experts for promoting COVID-19 research

Authors: Anastasia Krithara; Anastasios Nentidis; Eirini Vandorou; Georgios Katsimpras; Yannis Almirantis; Magda Arnal; Adomas Bunevicius; +11 Authors

BioASQ Synergy: a dialogue between question-answering systems and biomedical experts for promoting COVID-19 research

Abstract

Abstract Objective This article presents the novel BioASQ Synergy research process which aims to facilitate the interaction between biomedical experts and automated question-answering systems. Materials and Methods The proposed research allows systems to provide answers to emerging questions, which in turn are assessed by experts. The assessment of the experts is fed back to the systems, together with new questions. With this iteration, we aim to facilitate the incremental understanding of a developing problem and contribute to solution discovery. Results The results suggest that the proposed approach can assist researchers to navigate available resources. The experts seem to be very satisfied with the quality of the ideal answers provided by the systems, suggesting that such systems are already useful in answering open research questions. Discussion BioASQ Synergy aspires to provide a tool that gives the experts easy and personalized access to the latest findings in a fast-growing corpus of material. Conclusion In this article, we envisioned BioASQ Synergy as a continuous dialogue between experts and systems to issue open questions. We ran an initial proof-of-concept of the approach, in order to evaluate its usefulness, both from the side of the experts, as well as from the side of the participating systems.

Countries
Belgium, Spain, Greece
Keywords

Technology, Biomedical Research, Biomedical information, 551, Research and Applications, 46 Information and computing sciences, biomedical experts, 09 Engineering, Question answering, Humans, Information Science & Library Science, Àrees temàtiques de la UPC::Informàtica::Intel·ligència artificial::Llenguatge natural, 11 Medical and Health Sciences, Computer Science, Information Systems, Science & Technology, 42 Health sciences, Biomedical experts, COVID-19, 32 Biomedical and clinical sciences, Health Care Sciences & Services, biomedical information, question answering, Computer Science, Computer Science, Interdisciplinary Applications, 08 Information and Computing Sciences, Life Sciences & Biomedicine, Medical Informatics

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selected citations
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This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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