Paper Title

Development of a Domain-specific Summarization Model for Patient Reports using Named Entity Recognition, Sentiment Analysis, and Abstraction-based Summarization Techniques

Authors

A.BABISHA , RASHINI.H , KEERTHE.B

Keywords

Summarization, Patient Information, Customized Approach, Domain- Specific Knowledge, Machine Learning.

Abstract

The ability to effectively summarize patient information is critical for healthcare providers who must make informed decisions about patient care. In this paper, we present a customized summarization model designed specifically for patient information. Our model takes as input a variety of patient information, including demographic information, medical history, diagnosis, treatment plan, and response to treatment, and generates a concise summary that is easily understandable to anyone reading it. To develop our model, we utilized domain specific knowledge, including medical terminology and treatment protocols, and leveraged machine learning techniques such as natural language processing and deep learning. Our model was evaluated on a sample of patient reports and achieved high levels of accuracy and precision, demonstrating its effectiveness for summarizing patient information.

How To Cite

"Development of a Domain-specific Summarization Model for Patient Reports using Named Entity Recognition, Sentiment Analysis, and Abstraction-based Summarization Techniques", TIJER - TIJER - INTERNATIONAL RESEARCH JOURNAL (www.TIJER.org), ISSN:2349-9249, Vol.11, Issue 2, page no.28-33, February-2024, Available :https://tijer.org/TIJER/papers/TIJERB001005.pdf

Issue

Volume 11 Issue 2, February-2024

Pages : 28-33

Other Publication Details

Paper Reg. ID: TIJER_150950

Published Paper Id: TIJERB001005

Downloads: 000272

Research Area: Science and Technology

Country: THIRUVALLUR, TAMILNADU, India

Published Paper PDF: https://tijer.org/TIJER/papers/TIJERB001005

Published Paper URL: https://tijer.org/TIJER/viewpaperforall?paper=TIJERB001005

About Publisher

ISSN: 2349-9249 | IMPACT FACTOR: 8.57 Calculated By Google Scholar | ESTD YEAR: 2014

An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.57 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator

Publisher: TIJER (IJ Publication) Janvi Wave

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