Volume 3, Issue 3 · IJARST · ISSN 2319-1783 / 2320-1126

An Adaptive Machine Learning Approach for Semantic Analysis to Extract Medical Knowledge

An Adaptive Machine Learning Approach for Semantic Analysis to Extract Medical Knowledge is an open-access, peer-reviewed research paper by Anushaa Putta*and RamaJanaki Devi Ramireddy, published in Volume 3, Issue 3 of the International Journal of Advanced Research in Science and Technology (IJARST), a UGC-approved journal (Print ISSN 2319-1783, Online ISSN 2320-1126).

Author

Anushaa Putta*and RamaJanaki Devi Ramireddy

Abstract

Machine learning approach over medical datasets is still an important research issue in recent days of technology in medical field. In our approach we are proposing an efficient classification approach for analysis of testing samples with training samples. Initially we train the medical abstracts by identifying disease and treatment and then forwards these informative and non informative sentences towards word of bag (Cure, prevent, etc.) to extract positive and negative sentences and finally update them in database for future classification of testing samples.

DOI

https://doi.org/10.62226/ijarst20140335

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How do you cite this paper?

Anushaa Putta*and RamaJanaki Devi Ramireddy — “An Adaptive Machine Learning Approach for Semantic Analysis to Extract Medical Knowledge.” International Journal of Advanced Research in Science and Technology (IJARST), Volume 3, Issue 3. DOI: https://doi.org/10.62226/ijarst20140335.

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