Research on text data mining of hospital patient records within Electronic Medical Records

Chen J, Podchiyska T, Altman R. OrderRex: clinical order decision support and outcome predictions by data-mining electronic medical records. J Am Med Inform Assoc 2016;23:339-48 https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5009921/ Miotto R, Li L, Kidd BA, Dudley JT. Deep Patient: An Unsupervised Representation to Predict the Future of Patients from the Electronic Health Records. Sci Rep 2016;6:26094 https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4869115/ Prasser F, Kohlmayer F, Kuhn KA. The Importance of Context: Risk-based De-identification of Biomedical Data. Methods Inf Med 2016;55:347-55 https://methods.schattauer.de/en/contents/archivestandard/issue/2382/manuscript/25994.ht Saez C, Zurriaga O, Perez-Panades J, Melchor I, Robles M, Garcia-Gomez JM. Applying probabilistic temporal and multisite data quality control methods to a public health mortality registry in Spain: a systematic approach to quality control of repositories. J Am Med Inform Assoc 2016;23:1085-95 https://academic.oup.com/jamia/article-lookup/doi/10.1093/jamia/ocw010

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Information Visualization with Text Data Mining for Knowledge Discovery Tools in Bioinformatics

Key Engineering Materials ◽

10.4028/www.scientific.net/kem.277-279.259 ◽

2005 ◽

Vol 277-279 ◽

pp. 259-265

Author(s):

Jin Ah Park ◽

Chang Su Lee ◽

Jong C. Park

Keyword(s):

Data Mining ◽

3D Visualization ◽

Three Dimensional ◽

Mitogen Activated Protein Kinase ◽

Text Data ◽

Text Data Mining ◽

Visualization System ◽

Source Data ◽

Mitogen Activated Protein ◽

Available Information

An abundant amount of information is produced in the digital domain, and an effective information extraction (IE) system is required to surf through this sea of information. In this paper, we show that an interactive visualization system works effectively to complement an IE system. In particular, three-dimensional (3D) visualization can turn a data-centric system into a user-centric one by facilitating the human visual system as a powerful pattern recognizer to become a part of the IE cycle. Because information as data is multidimensional in nature, 2D visualization has been the preferred mode. However, we argue that the extra dimension available for us in a 3D mode provides a valuable space where we can pack an orthogonal aspect of the available information. As for candidates of this orthogonal information, we have considered the following two aspects: 1) abstraction of the unstructured source data, and 2) the history line of the discovery process. We have applied our proposal to text data mining in bioinformatics. Through case studies of data mining for molecular interaction in the yeast and mitogen-activated protein kinase pathways, we demonstrate the possibility of interpreting the extracted results with a 3D visualization system.

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RightJob: Application of Text Data Mining to Curriculum Selection and Development

Academy of Management Proceedings ◽

10.5465/ambpp.2019.10848abstract ◽

2019 ◽

Vol 2019 (1) ◽

pp. 10848

Author(s):

Andres Fortino ◽

Roy Lowrance ◽

Qitong Zhong ◽

WeiChieh Huang

Keyword(s):

Data Mining ◽

Text Data ◽

Text Data Mining

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