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BioASQ: A Challenge on Large-Scale Biomedical Semantic Indexing and Question Answering [chapter]

Georgios Balikas, Anastasia Krithara, Ioannis Partalas, George Paliouras
2015 Lecture Notes in Computer Science  
This article provides an overview of BIOASQ, a new competition on biomedical semantic indexing and question answering (QA).  ...  BIOASQ encourages participants to adopt semantic indexing as a means to combine multiple information sources and to facilitate the matching of questions to answers.  ...  It will set up a challenge on biomedical semantic indexing and QA, which will require the participants to semantically index content from large-scale biomedical sources (e.g., MEDLINE) and to assemble  ... 
doi:10.1007/978-3-319-24471-6_3 fatcat:evlqerqosnbl7j7o46a7pertsu

Semantic role labeling tools for biomedical question answering: a study of selected tools on the BioASQ datasets

Fabian Eckert, Mariana Neves
2018 Proceedings of the 6th BioASQ Workshop A challenge on large-scale biomedical semantic indexing and question answering   unpublished
We analyzed the performance of three SRL tools (BioKIT, BIOSMILE and PathLSTM) on 1776 questions from the BioASQ challenge.  ...  Question answering (QA) systems usually rely on advanced natural language processing components to precisely understand the questions and extract the answers.  ...  Semantic Role Labeling on Biomedical Text Corpora , a corpus with PASs for the biomedical domain.  ... 
doi:10.18653/v1/w18-5302 fatcat:bpp7gpioubayrcogf7ooqqr7xm

UNCC QA: Biomedical Question Answering system

Abhishek Bhandwaldar, Wlodek Zadrozny
2018 Proceedings of the 6th BioASQ Workshop A challenge on large-scale biomedical semantic indexing and question answering   unpublished
In this paper, we detail our submission to the BioASQ competition's Biomedical Semantic Question and Answering task.  ...  Our contributions are named-entity based method for answering factoid and list questions, and an extractive summarization techniques for building paragraph-sized summaries, based on lexical chains.  ...  We would like to thank the referees for their comments and suggestions. All the remaining faults are ours.  ... 
doi:10.18653/v1/w18-5308 fatcat:vpmqx6m2uvfrvadniitkp4juju

MindLab Neural Network Approach at BioASQ 6B

Andrés Rosso-Mateus, Fabio A. González, Manuel Montes-y-Gómez
2018 Proceedings of the 6th BioASQ Workshop A challenge on large-scale biomedical semantic indexing and question answering   unpublished
Biomedical Question Answering is concerned with the development of methods and systems that automatically find answers to natural language posed questions.  ...  In this work, we describe the system used in the BioASQ Challenge task 6b for document retrieval and snippet retrieval (with particular emphasis in this subtask).  ...  Agreement N • . 727, 2016 provided financial as well as logistical and planning support.  ... 
doi:10.18653/v1/w18-5305 fatcat:j262y45ga5eizlywuxo4qmak3a

AUEB at BioASQ 6: Document and Snippet Retrieval

George Brokos, Polyvios Liosis, Ryan McDonald, Dimitris Pappas, Ion Androutsopoulos
2018 Proceedings of the 6th BioASQ Workshop A challenge on large-scale biomedical semantic indexing and question answering   unpublished
We present AUEB's submissions to the BioASQ 6 document and snippet retrieval tasks (parts of Task 6b, Phase A).  ...  Our systems scored at the top or near the top for all batches of the challenge, highlighting the effectiveness of deep learning for these tasks.  ...  Introduction BioASQ (Tsatsaronis et al., 2015) is a biomedical document classification, document retrieval, and question answering competition, currently in its sixth year. 1 We provide an overview  ... 
doi:10.18653/v1/w18-5304 fatcat:prwi7zz4sffjjlho5m6wkef3pe

Results of the sixth edition of the BioASQ Challenge

Anastasios Nentidis, Anastasia Krithara, Konstantinos Bougiatiotis, Georgios Paliouras, Ioannis Kakadiaris
2018 Proceedings of the 6th BioASQ Workshop A challenge on large-scale biomedical semantic indexing and question answering   unpublished
The BioASQ challenge aims at the promotion of systems and methodologies through the organization of a challenge on two tasks: semantic indexing and question answering.  ...  This paper presents the results of the sixth edition of the BioASQ challenge.  ...  Acknowledgments The sixth edition of BioASQ is supported by a conference grant from the NIH/NLM (number 1R13LM012214-01) and sponsored by the Atypon Systems inc.  ... 
doi:10.18653/v1/w18-5301 fatcat:e7rrikmhfncbbk5ufnx3ndc4ey

Extraction Meets Abstraction: Ideal Answer Generation for Biomedical Questions

Yutong Li, Nicholas Gekakis, Qiuze Wu, Boyue Li, Khyathi Chandu, Eric Nyberg
2018 Proceedings of the 6th BioASQ Workshop A challenge on large-scale biomedical semantic indexing and question answering   unpublished
Biomedical Question Answering can automatically generate answers for a user's topic or question, significantly reducing the effort required to locate the most relevant information in a large document corpus  ...  The growing number of biomedical publications is a challenge for human researchers, who invest considerable effort to search for relevant documents and pinpointed answers.  ...  Biomedical Question Answering (BQA) systems can automatically generate ideal answers for a user's question, signif- * denotes equal contribution icantly reducing the effort required to locate the most  ... 
doi:10.18653/v1/w18-5307 fatcat:dqutt55gybchnbifz4ztfqac7a

Ontology-Based Retrieval & Neural Approaches for BioASQ Ideal Answer Generation

Ashwin Naresh Kumar, Harini Kesavamoorthy, Madhura Das, Pramati Kalwad, Khyathi Chandu, Teruko Mitamura, Eric Nyberg
2018 Proceedings of the 6th BioASQ Workshop A challenge on large-scale biomedical semantic indexing and question answering   unpublished
Generating a non-redundant, human-readable summary that satisfies the information need of a given biomedical question is the focus of the Ideal Answer Generation task, part of the BioASQ challenge.  ...  Biomedical Question Answering systems automatically identify the most relevant documents and pinpointed answers, given an information need expressed as a natural language question.  ...  Introduction In this paper, we describe our attempts to address the Ideal Answer Generation task of the sixth edition of the BioASQ challenge, 1 which is a large-scale semantic indexing and question answering  ... 
doi:10.18653/v1/w18-5310 fatcat:u7fcxm5uebex3noggpuq5qk3qm

An Adaption of BIOASQ Question Answering dataset for Machine Reading systems by Manual Annotations of Answer Spans

Sanjay Kamath, Brigitte Grau, Yue Ma
2018 Proceedings of the 6th BioASQ Workshop A challenge on large-scale biomedical semantic indexing and question answering   unpublished
BIOASQ Task B Phase B challenge focuses on extracting answers from snippets for a given question. The dataset provided by the organizers contains answers, but not all their variants.  ...  Henceforth a manual annotation was performed to extract all forms of correct answers.  ...  Conclusion and Future Work We present the importance of using all variants of answers in the snippets for adapting the Bioasq dataset to machine reading task format.  ... 
doi:10.18653/v1/w18-5309 fatcat:5beoo4qzs5ep7fjurh3lxmz2qu

AttentionMeSH: Simple, Effective and Interpretable Automatic MeSH Indexer

Qiao Jin, Bhuwan Dhingra, William Cohen, Xinghua Lu
2018 Proceedings of the 6th BioASQ Workshop A challenge on large-scale biomedical semantic indexing and question answering   unpublished
of BioASQ Task5a challenge -DeepMeSH.  ...  We propose a novel end-to-end model, AttentionMeSH, which utilizes deep learning and attention mechanism to index MeSH terms to biomedical text.  ...  The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.  ... 
doi:10.18653/v1/w18-5306 fatcat:ejvk4krrarbsrfqt6keax7j5gi

Macquarie University at BioASQ 6b: Deep learning and deep reinforcement learning for query-based summarisation

Diego Mollá
2018 Proceedings of the 6th BioASQ Workshop A challenge on large-scale biomedical semantic indexing and question answering   unpublished
This paper describes Macquarie University's contribution to the BioASQ Challenge (BioASQ 6b, Phase B).  ...  We focused on the extraction of the ideal answers, and the task was approached as an instance of query-based multi-document summarisation.  ...  Introduction The BioASQ Challenge 1 consists of various tasks related to biomedical semantic indexing and question answering (Tsatsaronis et al., 2015) .  ... 
doi:10.18653/v1/w18-5303 fatcat:tw64y4zlcbhprjsa3s2u4vxks4

BioASQ: Large-scale biomedical semantic indexing and question answering

Anastasios Nentidis Anastasia Krithara
2020 Zenodo  
The BioASQ challenge introduced two complementary tasks: (a) the automated indexing of large volumes of unlabeled data, primarily scientific articles, with biomedical concepts, (b) the processing of biomedical  ...  BioASQ[1] organizes a series of challenges that reward highly precise biomedical information access and machine learning systems, and thus ensures that the biomedical experts will have direct access to  ...  ΙNAREST II&T IB NCSR 'D' What is BioASQ A competition • BioASQ is a series of challenges on biomedical semantic indexing and question answering (QA). • Participants are required to semantically  ... 
doi:10.5281/zenodo.4043010 fatcat:yad74dgkwffbrcyftcrg4oqgxy

Overview of BioASQ 2020: The Eighth BioASQ Challenge on Large-Scale Biomedical Semantic Indexing and Question Answering [chapter]

Anastasios Nentidis, Anastasia Krithara, Konstantinos Bougiatiotis, Martin Krallinger, Carlos Rodriguez-Penagos, Marta Villegas, Georgios Paliouras
2020 Lecture Notes in Computer Science  
BioASQ is a series of challenges aiming at the promotion of systems and methodologies for large-scale biomedical semantic indexing and question answering.  ...  This year, the challenge has been extended with the introduction of a new task on medical semantic indexing in Spanish.  ...  Large-scale semantic indexing -Task 8a Biomedical semantic QA -Task 8b Task 8b aims at providing a realistic large-scale question answering challenge offering to the participating teams the opportunity  ... 
doi:10.1007/978-3-030-58219-7_16 fatcat:wekghiprdzc53ejvwxdvn5d2xq

Overview of BioASQ 2021: The ninth BioASQ challenge on Large-Scale Biomedical Semantic Indexing and Question Answering [article]

Anastasios Nentidis, Georgios Katsimpras, Eirini Vandorou, Anastasia Krithara, Luis Gasco, Martin Krallinger, Georgios Paliouras
2021 arXiv   pre-print
Advancing the state-of-the-art in large-scale biomedical semantic indexing and question answering is the main focus of the BioASQ challenge.  ...  In this year, a new question answering task, named Synergy, is introduced to support researchers studying the COVID-19 disease and measure the ability of the participating teams to discern information  ...  Overview of the Tasks In this year, the ninth version of the BioASQ challenge offered four tasks: (1) a large-scale biomedical semantic indexing task (task 9a), (2) a biomedical question answering task  ... 
arXiv:2106.14885v1 fatcat:uix2mc6jh5hg3jegwzfhwblzc4

Results of the First BioASQ Workshop

Ioannis Partalas, Éric Gaussier, Axel-Cyrille Ngonga Ngomo
2013 Conference and Labs of the Evaluation Forum  
Overview of the Tasks The challenge comprised two tasks: (1) a large-scale semantic indexing task (Task 1a) and (2) a question answering task (Task 1b).  ...  The first challenge consisted of two tasks: semantic indexing and question answering. 157 systems were registered by 12 different participants for the semantic indexing task, of which between 19 and 29  ...  The goal here was to provide a large-scale question answering challenge where the systems should be able to cope with all the stages of a question answering task, including the retrieval of relevant concepts  ... 
dblp:conf/clef/PartalasGN13 fatcat:w5i7xamhdrhunpxfbjz3d4wj4e
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