Text-mining in cancer research may help identify effective treatments

Hsiao, Yi-Wen; Lu, Tzu-Pin

doi:10.21037/tlcr.2019.12.20

Cited by 10 publications

(8 citation statements)

References 27 publications

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“…Thus, text mining which digitalizes textual data and enables them to be applied for text mining algorithms has a very important place in today's world. Text mining methods have become a frequently used method recently in the fields of medicine and biology (4,(6)(7)(8)(9)(10)(11)(12)(13) as well as in many fields. In a study conducted by Yu et al (13), investigating the genes and prognostic factors associated with breast cancer considering 708 genes in total which they obtained from the gene expression omnibus database, they created the transcription factor-target regulation and microRNA-target gene network using the text mining approach.…”

Section: Discussionmentioning

confidence: 99%

“…It has become a method commonly used in the fields of health, education, legal, customer relations, market surveys, and internal security to analyze numerous digital texts in a short time and to reach qualified information quickly (5). In particular, in recent studies on health, this method has been increasingly used (4,(6)(7)(8)(9)(10)(11)(12)(13).…”

Section: Sağlık Alanında Metin Madenciliği Yöntemimentioning

confidence: 99%

“…The basic strategy of computation mechanism that processes text-based information is to reduce natural language inputs being too much into a set of small categories (5). Text mining applications may include information retrieval, natural language processing (NLP), named entity recognition, pattern identified entities, coreference, relation, rule, event extractions, and sentimental analysis (9,15). The cross industry standard process for data mining (CRISP-DM), the most commonly used process in data mining, is also preferred in text mining.…”

Section: Sağlık Alanında Metin Madenciliği Yöntemimentioning

confidence: 99%

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Text Mining Method in the Field of Health

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Cangür

2020

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Objective: Text mining which digitalizes textual data and enables them to be applied for text mining algorithms has a very important place in today's world. The aim of this study was to introduce the text mining method and to show its application on a subject in the field of health. Methods: The text mining method was applied to the documents obtained separately from the most frequently used Pubmed database under two different titles as "humanand-cancer" and "mouse-and-cancer", and then to the combined documents, through the Knime program. Afterwards, the document classification was made using K nearest neighbor (K-NN) algorithm. Results: The prominent words were "cell" and "cancer" in tag cloud graphs. In both documents, the words such as "cell", "cancer", "tumor", "patient", whose frequency values were high, were observed to be high rates in the analysis performed after the data was merged. It was found that 255 of 600 test documents belonged to the humanand-cancer class and the remaining belonged to the mouse-and-cancer class, and the accuracy classification was 56.6% for the human-and-cancer-documents and 62.6% for the mouse-and-cancer-documents according to the F-criteria. It was determined that the document classification estimation by the K-NN algorithm was relatively successful with a rate of 59.8% however Cohen's kappa value was 19.7%, meaning that the fit was of a slight level. Conclusions: It was recommended to use the text mining method and to generalize its use in order to obtain information quickly and reliably in the health field where there were numerous digital and printed documents.

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Section: Discussionmentioning

confidence: 99%

Section: Sağlık Alanında Metin Madenciliği Yöntemimentioning

confidence: 99%

Section: Sağlık Alanında Metin Madenciliği Yöntemimentioning

confidence: 99%

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Text Mining Method in the Field of Health

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Cangür

2020

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“…Text mining method has become a powerful means to extract information and knowledge from a large number of scientific literature, which can provide clues for the repositioning of existing drugs and help for effective treatment in the future [ 19 ]. The development of potential effects of traditional drugs can not only contribute to the discovery of new and more effective agents but also present tremendous opportunities for studying novel targets of pharmacology and break through the bottleneck of disease treatment [ 20 ].…”

Section: Introductionmentioning

confidence: 99%

Searching for essential genes and drug discovery in breast cancer and periodontitis via text mining and bioinformatics analysis

et al. 2021

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“…How genes in this group work cooperatively to regulate or stimulate the complex biological function in different cellular status, however, often remains a mystery. Based on scientific studies or other text mining techniques (3,4), several public databases, such as KEGG (5), BioGRID (6) and STRING (7), have already annotated biological functions as pathways and the interactions within the molecular network. Therefore, it is possible to examine if the estimated correlation from the raw data is in conformity with the information retrieved from those public databases.…”

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confidence: 99%