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Application of Text Mining in the Biomedical Domain
Methods, 2015In recent years the amount of experimental data that is produced in biomedical research and the number of papers that are being published in this field have grown rapidly. In order to keep up to date with developments in their field of interest and to interpret the outcome of experiments in light of all available literature, researchers turn more and ...
Wynand Alkema
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Frontiers of Biomedical Text Mining: Current Progress. [PDF]
Briefings in Bioinformatics, 2007 It is now almost 15 years since the publication of the first paper on text mining in the genomics domain, and decades since the first paper on text mining in the medical domain. Enormous progress has been made in the areas of information retrieval, evaluation methodologies and resource construction.
Pierre Zweigenbaum, Dina Demner-Fushman
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Biomedical Text Mining and Its Applications in Cancer Research
Journal of Biomedical Informatics, 2013 Cancer is a malignant disease that has caused millions of human deaths. Its study has a long history of well over 100years. There have been an enormous number of publications on cancer research. This integrated but unstructured biomedical text is of great value for cancer diagnostics, treatment, and prevention.
Fei Zhu +2 more
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Adversarial Constraint Evaluation on Biomedical Text Mining
2021Language model pre-training has been shown to be effective for improving many NLP tasks, relying on its ability of representing complex context. The BERT language model (LM) has achieved remarkable results in standard performance indicators for tasks such as Named Entity Recognition (NER) and Semantic Text Similarity (STS), and has made significant ...
Yashen Wang, Huanhuan Zhang
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Text mining patents for biomedical knowledge
Drug Discovery Today, 2016Biomedical text mining of scientific knowledge bases, such as Medline, has received much attention in recent years. Given that text mining is able to automatically extract biomedical facts that revolve around entities such as genes, proteins, and drugs, from unstructured text sources, it is seen as a major enabler to foster biomedical research and drug
Raul, Rodriguez-Esteban +1 more
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Development of a Machine Learning Framework for Biomedical Text Mining [PDF]
Advances in Intelligent Systems and Computing, 2016 Biomedical text mining (BTM) aims to create methods for searching and structuring knowledge extracted from biomedical literature. Named entity recognition (NER), a BTM task, seeks to identify mentions to biological entities in texts. Dictionaries, regular expressions, natural language processing and machine learning (ML) algorithms are used in this ...
Miguel Rocha +2 more
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Status of text-mining techniques applied to biomedical text
Drug Discovery Today, 2006Scientific progress is increasingly based on knowledge and information. Knowledge is now recognized as the driver of productivity and economic growth, leading to a new focus on the role of information in the decision-making process. Most scientific knowledge is registered in publications and other unstructured representations that make it difficult to ...
Erhardt, R. A. A. +2 more
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Biomedical Text Mining: Experience and Practical Approach
2015 3rd International Conference on Applied Computing and Information Technology/2nd International Conference on Computational Science and Intelligence, 2015The fields of biomedical researches included biology and medicine has resulted in a sheer amount of published reports, and papers. Above all biomedical text mining has emerged as a vital research domain that has an impact in the project development of these research areas.
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Biomedical Hypothesis Generation by Text Mining and Gene Prioritization
Protein & Peptide Letters, 2013Text mining methods can facilitate the generation of biomedical hypotheses by suggesting novel associations between diseases and genes. Previously, we developed a rare-term model called RaJoLink (Petric et al, J. Biomed. Inform. 42(2): 219-227, 2009) in which hypotheses are formulated on the basis of terms rarely associated with a target domain.
Petrič I +3 more
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Ontology Design for Biomedical Text Mining
2007Text Mining in biology and biomedicine requires a large amount of domain-specific knowledge. Publicly accessible resources hold much of the information needed, yet their practical integration into natural language processing (NLP) systems is fraught with manifold hurdles, especially the problem of semantic disconnectedness throughout the various ...
René Witte +2 more
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