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The TREC 2019 Deep Learning task aims at studying information retrieval in a large training data regime. It includes two tasks: the document ranking task (1) and the passage ranking task (2). ... The SIB Text Mining group participated at the full document ranking subtask (1a). In order to retrieve pertinent documents in the 3.2 million documents corpus, our strategy was two-fold. ... Introduction The SIB Text Mining group  , at the Swiss Institute of Bioinformatics in Geneva, has a long history of participation in TREC campaigns, including TREC Genomics  , TREC Medical Records ...dblp:conf/trec/KnafouJMTR19 fatcat:2bbmxmh5bffflglbn3sbktsve4
Thanks to recent efforts by the text mining community, biocurators have now access to plenty of good tools and Web interfaces for identifying and visualizing biomedical entities in literature. ... A couple of works recently focused on literature triage based on deep learning algorithms, based on convolutional neural networks (22, 23) , resulting on higher precisions in result sets. ... Case 2: information retrieval for precision medicine The 2019 TREC Precision Medicine track focused on the case of providing clinical decision support for cancer patients with genetic variations that might ...doi:10.1093/nar/gkaa328 pmid:32379317 pmcid:PMC7319474 fatcat:wnwek6k6fngerlm2txpqc4r2si
a new European starting community of key research infrastructures, establishing open science practices in the domain of biodiversity through provision of access to data, associated tools and services at ... BiCIKL will provide for the first time access and tools for seamless linking and usage tracking of data along the line: specimens > sequences > species > analytics > publications > biodiversity ... He worked as scientific researcher at the University of Amsterdam, Netherlands Institute for Sea Research, the Alfred Wegener Institute for Polar Research, and as managing director at ETI Biodiversity ...doi:10.3897/rio.8.e81136 fatcat:4owwssl7zzfzna6likizigcv7u