Results 41 to 50 of about 73,896 (143)
Text mining brain imaging reports
Background With the improvements to text mining technology and the availability of large unstructured Electronic Healthcare Records (EHR) datasets, it is now possible to extract structured information from raw text contained within EHR at reasonably high
Beatrice Alex +5 more
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A Survey of the Applications of Text Mining for the Food Domain
In the food domain, text mining techniques are extensively employed to derive valuable insights from large volumes of text data, facilitating applications such as aiding food recalls, offering personalized recipes, and reinforcing food safety regulation.
Shufeng Xiong +4 more
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Text Mining for Protein Docking.
The rapidly growing amount of publicly available information from biomedical research is readily accessible on the Internet, providing a powerful resource for predictive biomolecular modeling.
Varsha D Badal +2 more
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Monitoring interaction and collective text production through text mining [PDF]
This article presents the Concepts Network tool, developed using text mining technology. The main objective of this tool is to extract and relate terms of greatest incidence from a text and exhibit the results in the form of a graph.
Macedo, Alexandra Lorandi +2 more
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Biomedical text mining promises to assist biologists in quickly navigating the combined knowledge in their domain. This would allow improved understanding of the complex interactions within biological systems and faster hypothesis generation.
Kishore R. Anekalla +5 more
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Review of the Approaches and Techniques of Text Mining in Clinical Documentation
Introduction: With the extensive use of electronic medical records systems, a large amount of medical text data is produced daily in the hospitals and other medical environments that organizing this text information is important and necessary.
Farzaneh Feizmanesh, Ali Asghar Safaei
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Using Statistical Properties to Enhance Text Categorization [PDF]
Statistical properties extracted from text are useful in many areas. Knowing who authored some text or knowing the category of a text is among the uses of collecting such statistics.
Rached Zantout, Ziad Osman
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Text Mining Infrastructure in R
During the last decade text mining has become a widely used discipline utilizing statistical and machine learning methods. We present the tm package which provides a framework for text mining applications within R.
Kurt Hornik, Ingo Feinerer, David Meyer
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Text Mining YouTube Comment Data with Wordfish in R
In this lesson, you will learn how to download YouTube video comments and use the R programming language to analyze the dataset with Wordfish, an algorithm designed to identify opposing ideological perspectives within a corpus.
Alex Wermer-Colan +2 more
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Text Mining in Python through the HTRC Feature Reader
We introduce a toolkit for working with the 13.6 million volume Extracted Features Dataset from the HathiTrust Research Center. You will learn how to peer at the words and trends of any book in the collection, while developing broadly useful Python data ...
Peter Organisciak, Boris Capitanu
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