Dietrich Rebholz-Schuhmann mainly focuses on Information retrieval, Annotation, Text mining, Data science and Controlled vocabulary. His Information retrieval research incorporates elements of Sentence, Artificial intelligence, Natural language processing and Context. His research integrates issues of Document Structure Description, Set, Biomedical text mining and Conceptualization in his study of Annotation.
Dietrich Rebholz-Schuhmann combines subjects such as Biological network and Bioinformatics with his study of Data science. His Bioinformatics research includes elements of Information extraction, Textual information and Complex network. The various areas that Dietrich Rebholz-Schuhmann examines in his Controlled vocabulary study include Biological database and Thesaurus.
Information retrieval, Artificial intelligence, Natural language processing, Data science and Annotation are his primary areas of study. His studies deal with areas such as Text mining and Identification as well as Information retrieval. As part of the same scientific family, he usually focuses on Artificial intelligence, concentrating on Domain and intersecting with Biomedicine.
His work is dedicated to discovering how Natural language processing, Named-entity recognition are connected with Conditional random field and other disciplines. His Data science study frequently intersects with other fields, such as Biomedical text mining. As a member of one scientific family, Dietrich Rebholz-Schuhmann mostly works in the field of Annotation, focusing on UniProt and, on occasion, RDF.
Dietrich Rebholz-Schuhmann mostly deals with Artificial intelligence, Cluster analysis, Linked data, Computational biology and Information retrieval. His work carried out in the field of Artificial intelligence brings together such families of science as Machine learning and Gene expression. The Cluster analysis study combines topics in areas such as Semantics, World Wide Web and Natural language processing.
His study on Computational biology also encompasses disciplines like
Dietrich Rebholz-Schuhmann spends much of his time researching Pneumonia, Radiography, F1 score, Clinical Practice and X ray image. Dietrich Rebholz-Schuhmann incorporates a variety of subjects into his writings, including Pneumonia, Coronavirus disease 2019, Radiology, Medical physics, Deep neural networks and Predictive value.
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Text processing through Web services
Dietrich Rebholz-Schuhmann;Miguel Arregui;Sylvain Gaudan;Harald Kirsch.
EBIMed---text crunching to gather facts for proteins from Medline
Dietrich Rebholz-Schuhmann;Harald Kirsch;Miguel Arregui;Sylvain Gaudan.
Text-mining solutions for biomedical research: enabling integrative biology.
Dietrich Rebholz-Schuhmann;Anika Oellrich;Robert Hoehndorf.
Nature Reviews Genetics (2012)
Facts from text--is text mining ready to deliver?
Dietrich Rebholz-Schuhmann;Harald Kirsch;Francisco Couto.
PLOS Biology (2005)
Automatic recognition of conceptualization zones in scientific articles and two life science applications
Maria Liakata;Shyamasree Saha;Simon Dobnik;Colin Batchelor.
Assessment of disease named entity recognition on a corpus of annotated sentences
Antonio Jimeno;Ernesto Jimenez-Ruiz;Vivian Lee;Sylvain Gaudan.
BMC Bioinformatics (2008)
CALBC silver standard corpus.
Dietrich Rebholz-Schuhmann;Antonio José Jimeno Yepes;Erik M Van Mulligen;Ning Kang.
Journal of Bioinformatics and Computational Biology (2010)
Text mining for biology - the way forward: opinions from leading scientists
Russ B. Altman;Casey M. Bergman;Judith A. Blake;Christian Blaschke.
Genome Biology (2008)
Resolving abbreviations to their senses in Medline
S. Gaudan;H. Kirsch;D. Rebholz-Schuhmann.
Dolf Trieschnigg;Piotr Pezik;Vivian Lee;Franciska de Jong.
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