Constituency Parser for Clinical Narratives using NLP
Anjali Kedawat1, A. Senthil2
1Anjali Kedawat*, Department of CSE, Gitam University, Visakhapatnam, India
2Dr. A. Senthil, Department of CSE, Mody University, Laxmangarh, India.
Manuscript received on December 15, 2019. | Revised Manuscript received on December 22, 2019. | Manuscript published on January 10, 2020. | PP: 2277-2279 | Volume-9 Issue-3, January 2020. | Retrieval Number: C8865019320/2020©BEIESP | DOI: 10.35940/ijitee.C8865.019320
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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: Clinical parsing is useful in medical domain .Clinical narratives are difficult to understand as it is in unstructured format .Medical Natural language processing systems are used to make these clinical narratives in readable format. Clinical Parser is the combination of natural language processing and medical lexicon .For making clinical narrative understandable parsing technique is used .In this paper we are discussing about constituency parser for clinical narratives, which is based on phrase structured grammar. This parser convert unstructured clinical narratives into structured report. This paper focus on clinical sentences which is in unstructured format after parsing convert into structured format. For each sentence recall ,precision and bracketing f- measure are calculated .
Keywords: Clinical Narratives Constituency Parser, Phrase Structured Grammar, Probabilistic Context free Grammar
Scope of the Article: Probabilistic Models and Methods