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Anatomical entity mention recognition at literature scale

Sampo Pyysalo, Sophia Ananiadou
2013 Computer applications in the biosciences : CABIOS  
We next present the ontological basis, task setting and basic system architecture applied in our work.  ...  Results: We present AnatomyTagger, a machine learning-based system for anatomical entity mention recognition.  ...  , Rafal Rak for help with the web interface, Naoaki Okazaki and Han-Cheol Cho for introducing the label bias feature to CRFsuite and NERsuite tagging, Pontus Stenetorp and Hubert Soyer for help in inducing  ... 
doi:10.1093/bioinformatics/btt580 pmid:24162468 pmcid:PMC3957068 fatcat:itgzta3db5e2jiduvszpcaaclu

TaxoNERD: deep neural models for the recognition of taxonomic entities in the ecological and evolutionary literature [article]

Nicolas Le Guillarme, Wilfried Thuiller
2021 bioRxiv   pre-print
In recent years, deep learning-based NER systems have become ubiqutous, yielding state-of-the-art results in the general and biomedical domains.  ...  Tools are needed to automatically extract useful information from the ever-growing corpus of ecological texts and feed this information to open data repositories.  ...  The two models use the same two-layer architecture as spaCy's NER models but differ in the architecture of their embedding 182 (a) Architecture of TaxoNERD's en_ner_eco_md NER model.  ... 
doi:10.1101/2021.06.08.444426 fatcat:l2epu7suznc4taiknapvf73j44

The Origin of the Year 2000 Date Problem: an alternative hypothesis

Richard Kingsford, Leone Dunn
1999 Australasian Journal of Information Systems  
This paper aims to identify the primary origin of the year 2000 date problem, in which many computer-based systems may fail because they cannot correctly interpret two-digit year dates which lie in and  ...  The paper proposes a hypothesis within a cultural anthropological framework that the fundamental origin of the problem lay in a pre-existing, commonplace norm of Western culture -the pervasive use of two-digit  ...  In other cases a system was redeveloped in relational database or client/server form, and the old data or data model migrated to the new system (Gartner 1997; Johnston 1998) .  ... 
doi:10.3127/ajis.v6i2.309 fatcat:6766y2ojybafpidfuyrdzosrki

OrganismTagger: detection, normalization and grounding of organism entities in biomedical documents

N. Naderi, T. Kappler, C. J. O. Baker, R. Witte
2011 Bioinformatics  
In particular, our system combines a novel machine-learning approach with rule-based and lexical methods for detecting strain mentions in documents.  ...  In addition, such a system must resolve abbreviations and acronyms, assign the scientific name and if possible link the detected mention to the NCBI Taxonomy database for further semantic queries and literature  ...  Laurila are acknowledged for critical reading of the article and valuable suggestions. We also thank Martin Gerner for providing us with the Linnaeus corpus.  ... 
doi:10.1093/bioinformatics/btr452 pmid:21828087 fatcat:442zmuf7ffduxdelbayex7acn4

Classification of very high-resolution remote sensing imagery using a fully convolutional network with global and local context information enhancements

Huanjun Hu, Zheng Li, Lin Li, Hui Yang, Haihong Zhu
2020 IEEE Access  
In the DGEN architecture, a global attention enhancement module is developed for context acquisition, and a local attention fusion module is designed for detail selection.  ...  In this study, a dual attention mechanism is introduced and embedded into densely connected convolutional networks (DenseNets) to form a dense-global-entropy network (DGEN) for the semantic segmentation  ...  Yao (Anhui University) for providing data preprocessing.  ... 
doi:10.1109/access.2020.2964760 fatcat:54vizivkunhlfdrwfuibrrcrsy

Named Entity Recognition and Relation Detection for Biomedical Information Extraction

Nadeesha Perera, Matthias Dehmer, Frank Emmert-Streib
2020 Frontiers in Cell and Developmental Biology  
This information can be integrated into networks to summarize large-scale details on a particular biomedical or clinical problem, which is then amenable for easy data management and further analysis.  ...  Since there is currently no automatic archiving of the obtained results, much of this information remains buried in textual details not readily available for further usage or analysis.  ...  Then we review relation inferring methods in section 3, strength, and polarity analysis in section 4 and Data Integration and Visualization in section 5.  ... 
doi:10.3389/fcell.2020.00673 pmid:32984300 pmcid:PMC7485218 fatcat:khclwjfykjfi3jktvrbuliwidm

HunFlair: An Easy-to-Use Tool for State-of-the-Art Biomedical Named Entity Recognition [article]

Leon Weber, Mario Sänger, Jannes Münchmeyer, Maryam Habibi, Ulf Leser, Alan Akbik
2020 arXiv   pre-print
Summary: Named Entity Recognition (NER) is an important step in biomedical information extraction pipelines.  ...  Tools for NER should be easy to use, cover multiple entity types, highly accurate, and robust towards variations in text genre and style.  ...  Embeddings We use two types of word embeddings for HunFlair, (I) Flair embeddings based on a character-level language model (LM) and (II) fastText embeddings.  ... 
arXiv:2008.07347v2 fatcat:pn7jvhgrf5bivmrmedieeu6gre

INAS: Interactive Argumentation Support for the Scientific Domain of Invasion Biology

Tina Heger, Sina Zarrieß, Alsayed Algergawy, Jonathan Jeschke, Birgitta König-Ries
2022 Research Ideas and Outcomes  
publication abstracts (and data) to these hypotheses; and (iii) an interactive system that supports users in refining their initial, potentially underdeveloped hypothesis.  ...  According to argumentation theory, the starting point of an argument is a claim, and also data that serves as a basis for the claim.  ...  Acknowledgements We thank the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) for funding this project (Project number 455913229).  ... 
doi:10.3897/rio.8.e80457 fatcat:nzuvw7ogijb4npxc2uwflrlnyi

Deep learning with word embeddings improves biomedical named entity recognition

Maryam Habibi, Leon Weber, Mariana Neves, David Luis Wiegandt, Ulf Leser
2017 Bioinformatics  
On average, F1-score of LSTM-CRF is 5% above that of the baselines, mostly due to a sharp increase in recall.  ...  Furthermore, features are often optimized for a specific gold standard corpus, which makes extrapolation of quality measures difficult.  ...  Acknowledgements We are grateful to the Federal Ministry for Economic Affairs and Energy (BMWi) for its financial support through the BioPatent project [KF2205219BZ4], the Federal Ministry for Research  ... 
doi:10.1093/bioinformatics/btx228 pmid:28881963 pmcid:PMC5870729 fatcat:qemlnwmacbbcbeinqngjkh2rny

Jahuel: A Formal Framework for Software Synthesis [chapter]

I. Assayad, V. Bertin, F. -X. Defaut, Ph. Gerner, O. Quévreux, S. Yovine
2005 Lecture Notes in Computer Science  
For instance, a typical industrial practice for exploiting multiprocessor architectures for synchronous programs consists in manually cutting the code into pieces, and adding hand-written wrappers.  ...  A very common practice consists in using a language with no support for concurreny or time (e.g., C), together with specific libraries or system calls (e.g., POSIX threads or MPI [10]) provided by the  ...  We thank the anonymous reviewers for the helpful remarks.  ... 
doi:10.1007/11576280_15 fatcat:mrlvmx46njbuhm53pkau464zoq

Fully Automatic Wound Segmentation with Deep Convolutional Neural Networks [article]

Chuanbo Wang, DM Anisuzzaman, Victor Williamson, Mrinal Kanti Dhar, Behrouz Rostami, Jeffrey Niezgoda, Sandeep Gopalakrishnan, Zeyun Yu
2020 arXiv   pre-print
Various deep learning models have gained success in image analysis including semantic segmentation.  ...  in the treatment.  ...  In a typical CNN architecture, the input are processed by a sequence of convolutional layers and the output is gernerated by a fully connected layer that requires fixed-sized input.  ... 
arXiv:2010.05855v1 fatcat:zuqxqcskxnb4tdwdyh2dcoc6we

ScispaCy: Fast and Robust Models for Biomedical Natural Language Processing

Mark Neumann, Daniel King, Iz Beltagy, Waleed Ammar
2019 Proceedings of the 18th BioNLP Workshop and Shared Task  
Despite recent advances in natural language processing, many statistical models for processing text perform extremely poorly under domain shift.  ...  This paper describes scis-paCy, a new Python library and models for practical biomedical/scientific text processing, which heavily leverages the spaCy library.  ...  description of model architectures considered in this evaluation. ual words.  ... 
doi:10.18653/v1/w19-5034 dblp:conf/bionlp/NeumannKBA19 fatcat:7yucm2afanbf5m2yccjlzhe7vy

Relational logics and diagrams: 'No-scale conditions'
Relacione logike i dijagrami - stanja bez razmere (nemetrička stanja)

Dragana Ćirić
2016 SAJ. Serbian architectural journal  
The first part explains geometric and numeric relational figures/sets as taken for "principles of beauty and primary aesthetic quality of all things" in classical philosophy, science, and architecture.  ...  of nonlinearity and complexity by symmetry-breakings within non-metric systems.  ...  , traditional systems of architectural space encountered a problem of a proper integration and explanation of "intensities".  ... 
doi:10.5937/saj1603388q fatcat:nofua5qouvf3nc6qmzou3b7qv4

Fully automatic wound segmentation with deep convolutional neural networks

Chuanbo Wang, D. M. Anisuzzaman, Victor Williamson, Mrinal Kanti Dhar, Behrouz Rostami, Jeffrey Niezgoda, Sandeep Gopalakrishnan, Zeyun Yu
2020 Scientific Reports  
Various deep learning models have gained success in image analysis including semantic segmentation.  ...  The advantage of this model is its lightweight and less compute-intensive architecture. The performance is not compromised and is comparable to deeper neural networks.  ...  In a typical CNN architecture, the input are processed by a sequence of convolutional layers and the output is gernerated by a fully connected layer that requires fixed-sized input.  ... 
doi:10.1038/s41598-020-78799-w pmid:33318503 fatcat:dt7t4wvcwjatnkpr5b73jvodby

Large-scale extraction of brain connectivity from the neuroscientific literature

Renaud Richardet, Jean-Cédric Chappelier, Martin Telefont, Sean Hill
2015 Computer applications in the biosciences : CABIOS  
One challenge for modern neuroinformatics is finding methods to make the knowledge from the tremendous backlog of publications accessible for search, analysis and the integration of such data into computational  ...  The complete in litero extraction models are also evaluated against in vivo connectivity data from ABA with an estimated precision of 78%.  ...  Acknowledgements The authors thank Philémon Favrod for helping developing the nearest neighbours filter, Catherine Zwahlen for the reviews and Léon French and his coworkers for developing the WhiteText  ... 
doi:10.1093/bioinformatics/btv025 pmid:25609795 pmcid:PMC4426844 fatcat:3kebqepqdregfevwvi4eyieusm
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