Text Mining in Healthcare
Pranita Mahajan1, Dipti P. Rana2

1Pranita Mahajan, Assistant Professor, SIES Graduate School of Technology, Mumbai (Maharashtra), India.

2Dr. Dipti P. Rana, Assistant Professor, Sardar Vallabhbhai National Institute of Technology Surat (Gujarat), India.

Manuscript received on 05 December 2019 | Revised Manuscript received on 13 December 2019 | Manuscript Published on 31 December 2019 | PP: 436-443 | Volume-9 Issue-2S December 2019 | Retrieval Number: B11111292S19/2019©BEIESP | DOI: 10.35940/ijitee.B1111.1292S19

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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open-access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)

Abstract: In healthcare, data mining intensively and extensively becoming essential. Data mining applications can benefit all patients and the healthcare professionals. This paper starts with introducing data mining and the healthcare paradigm. This study confers various techniques of data mining in healthcare application domain. As the scope of the study is limited to text mining classification, state of art in particular to healthcare text mining classification is studied in detail with suggested improvements. Various issues and challenges owing to the type of data in healthcare are also discussed in detail with possible solutions. Finally, the paper highlights the need for personalized prescriptive systems for patients and healthcare professionals.

Keywords: NLP, Text Mining, Healthcare, Image Processing, Mobile App, Ontology, Prescriptive analysis, Descriptive Analysis, Predictive Analysis.
Scope of the Article: Text Mining