Classification of health care text using NLP and ML | Proceedings of the 5th International Conference on Information Management & Machine Intelligence (2024)

research-article

Author: Megha Sharma

November 2023

Article No.: 73, Pages 1 - 7

Published: 13 May 2024 Publication History

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    Abstract

    Now Health care industry grows so much and patient share their experience and those reviews help other to enhance and improving their knowledge. The trend of sharing thoughts, ideas, opinions, reviews, ratings, etc. on social media is growing, which gave lot of unstructured data. For these types of unstructured data supervised learning methods are good to extract something and improving the performance of the machine. NLP is the best method to extract information from the text data. Not only NLP but Machine Learning algorithm with NLP methods gave which is high accurate to train our machine for better prediction. In this paper UCI ML drug review dataset used from kaggle website and this dataset provide patients reviews on specified drugs along with some conditions. Bag of words and TF-IDF model along with Naïve bayes and Passive aggressive classifier algorithm to train and test the machine to classify the patients review text data. Our objective is to find which NLP model and ML algorithm is good based on the accuracy and is our machine able to classify patient review and predict condition based on the review.

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    Published In

    Classification of health care text using NLP and ML | Proceedings of the 5th International Conference on Information Management & Machine Intelligence (1)

    ICIMMI '23: Proceedings of the 5th International Conference on Information Management & Machine Intelligence

    November 2023

    1215 pages

    ISBN:9798400709418

    DOI:10.1145/3647444

    • Editors:
    • Dinesh Goyal,
    • Anil Kumar,
    • Dharm Singh,
    • Marcin Paprzycki,
    • Pooja Jain,
    • B. B. Gupta,
    • Uday Pratap Singh

    Copyright © 2023 ACM.

    Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [emailprotected].

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    Publication History

    Published: 13 May 2024

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    Author Tags

    1. Bag of words model
    2. Keywords— Text classification
    3. ML
    4. NLP
    5. Naïve bayes algorithm
    6. Passive aggressive classifier
    7. TF-IDF model

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    Classification of health care text using NLP and ML | Proceedings of the 5th International Conference on Information Management & Machine Intelligence (9)

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