Standard
Consumer Health Question Answering Using Off-the-Shelf Components: book chapter. / Pugachev, Alexander; Artemova, Ekaterina; Bondarenko, Alexander et al.
Advances in Information Retrieval: 45th European Conference on Information Retrieval: book. ed. / Jaap Kamps; Lorraine Goeuriot. Springer Cham, 2023. p. 571-579 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 13981).
Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review
Harvard
Pugachev, A, Artemova, E, Bondarenko, A
& Braslavski, P 2023,
Consumer Health Question Answering Using Off-the-Shelf Components: book chapter. in J Kamps & L Goeuriot (eds),
Advances in Information Retrieval: 45th European Conference on Information Retrieval: book. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 13981, Springer Cham, pp. 571-579.
https://doi.org/10.1007/978-3-031-28238-6_48APA
Vancouver
Author
Pugachev, Alexander ; Artemova, Ekaterina ; Bondarenko, Alexander et al. /
Consumer Health Question Answering Using Off-the-Shelf Components : book chapter. Advances in Information Retrieval: 45th European Conference on Information Retrieval: book. editor / Jaap Kamps ; Lorraine Goeuriot. Springer Cham, 2023. pp. 571-579 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).
BibTeX
@inproceedings{deed5240441545c6aefc62d7711a198a,
title = "Consumer Health Question Answering Using Off-the-Shelf Components: book chapter",
abstract = "In this paper, we address the task of open-domain health question answering (QA). The quality of existing QA systems heavily depends on the annotated data that is often difficult to obtain, especially in the medical domain. To tackle this issue, we opt for PubMed and Wikipedia as trustworthy document collections to retrieve evidence. The questions and retrieved passages are passed to off-the-shelf question answering models, whose predictions are then aggregated into a final score. Thus, our proposed approach is highly data-efficient. Evaluation on 113 health-related yes/no question and answer pairs demonstrates good performance achieving AUC of 0.82.",
author = "Alexander Pugachev and Ekaterina Artemova and Alexander Bondarenko and Pavel Braslavski",
note = "A. Pugachev{\textquoteright}s research was supported in part through computational resources of HPC facilities at HSE University [20]. A. Bondarenko{\textquoteright}s work was supported by the Deutsche Forschungsgemeinschaft (DFG) in the project “ACQuA 2.0: Answering Comparative Questions with Arguments” (project 376430233) as part of the priority program “RATIO: Robust Argumentation Machines” (SPP 1999). P. Braslavski{\textquoteright}s work was supported in part by the Ministry of Science and Higher Education of the Russian Federation (project 075-02-2022-877).",
year = "2023",
month = mar,
day = "17",
doi = "10.1007/978-3-031-28238-6_48",
language = "English",
isbn = "978-3-031-28237-9",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Cham",
pages = "571--579",
editor = "Jaap Kamps and Lorraine Goeuriot",
booktitle = "Advances in Information Retrieval: 45th European Conference on Information Retrieval",
address = "United Kingdom",
}
RIS
TY - GEN
T1 - Consumer Health Question Answering Using Off-the-Shelf Components
T2 - book chapter
AU - Pugachev, Alexander
AU - Artemova, Ekaterina
AU - Bondarenko, Alexander
AU - Braslavski, Pavel
N1 - A. Pugachev’s research was supported in part through computational resources of HPC facilities at HSE University [20]. A. Bondarenko’s work was supported by the Deutsche Forschungsgemeinschaft (DFG) in the project “ACQuA 2.0: Answering Comparative Questions with Arguments” (project 376430233) as part of the priority program “RATIO: Robust Argumentation Machines” (SPP 1999). P. Braslavski’s work was supported in part by the Ministry of Science and Higher Education of the Russian Federation (project 075-02-2022-877).
PY - 2023/3/17
Y1 - 2023/3/17
N2 - In this paper, we address the task of open-domain health question answering (QA). The quality of existing QA systems heavily depends on the annotated data that is often difficult to obtain, especially in the medical domain. To tackle this issue, we opt for PubMed and Wikipedia as trustworthy document collections to retrieve evidence. The questions and retrieved passages are passed to off-the-shelf question answering models, whose predictions are then aggregated into a final score. Thus, our proposed approach is highly data-efficient. Evaluation on 113 health-related yes/no question and answer pairs demonstrates good performance achieving AUC of 0.82.
AB - In this paper, we address the task of open-domain health question answering (QA). The quality of existing QA systems heavily depends on the annotated data that is often difficult to obtain, especially in the medical domain. To tackle this issue, we opt for PubMed and Wikipedia as trustworthy document collections to retrieve evidence. The questions and retrieved passages are passed to off-the-shelf question answering models, whose predictions are then aggregated into a final score. Thus, our proposed approach is highly data-efficient. Evaluation on 113 health-related yes/no question and answer pairs demonstrates good performance achieving AUC of 0.82.
UR - http://www.scopus.com/inward/record.url?partnerID=8YFLogxK&scp=85150946569
UR - https://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcAuth=tsmetrics&SrcApp=tsm_test&DestApp=WOS_CPL&DestLinkType=FullRecord&KeyUT=000995489700048
U2 - 10.1007/978-3-031-28238-6_48
DO - 10.1007/978-3-031-28238-6_48
M3 - Conference contribution
SN - 978-3-031-28237-9
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 571
EP - 579
BT - Advances in Information Retrieval: 45th European Conference on Information Retrieval
A2 - Kamps, Jaap
A2 - Goeuriot, Lorraine
PB - Springer Cham
ER -
