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Extraction and Summarization of Disease Details Using Text Summarization Techniques

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Intelligent Communication Technologies and Virtual Mobile Networks

Abstract

The application of machine learning (ML) and natural language processing (NLP) is being extensively used for research in the area of healthcare and biomedicine. This pattern goes especially in accordance with the course, and the healthcare system is headed in the highly networked world which includes the World Wide Web where the regular users and health experts conduct discourses on health issues. To glean knowledge from medical texts and discourses which are mostly in text in natural language, many text analysis frameworks and techniques have been designed. Those techniques do not produce a comprehensive summary about the content related to a disease from content available online. So in our work, we propose text summarization based on natural language processing algorithms combined with machine learning algorithms for extracting all information pertaining to a disease from online healthcare forums.

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Correspondence to Mamatha Balipa .

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Balipa, M., Yashvanth, S., Prakash, S. (2023). Extraction and Summarization of Disease Details Using Text Summarization Techniques. In: Rajakumar, G., Du, KL., Vuppalapati, C., Beligiannis, G.N. (eds) Intelligent Communication Technologies and Virtual Mobile Networks. Lecture Notes on Data Engineering and Communications Technologies, vol 131. Springer, Singapore. https://doi.org/10.1007/978-981-19-1844-5_50

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  • DOI: https://doi.org/10.1007/978-981-19-1844-5_50

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-19-1843-8

  • Online ISBN: 978-981-19-1844-5

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