Applied Intelligence and Computing
Topic Modelling of India’s Digital Healthcare Research Trend
Authors: Munikrishnappa Anilkumar, Manasa Nagabhushanam and Mallieswari R
Publishing Date: 10-11-2024
ISBN: 978-81-955020-9-7
Abstract
New advancements in information technology have had a tremendous impact on digital healthcare applications in the medical area. The study themes connected to digital healthcare technology and its intervention must be discovered and studied systematically. As a research gap, digital healthcare research in India has yet to be investigated thematically using topic modeling; in this context, the study employs topic modeling's Non-Negative Matrix Factorization algorithm to systematically generate digital health research themes in India. After preprocessing, the raw texts were transformed into Term Frequency-Inverse Document Frequency vectors. The Non-Negative Matrix Factorization approach from topic modeling was used for text classification. The k parameter was used for feature selection, yielding a set number of topics for semantic interpretation. Analysis of the research articles revealed that there has been considerable growth in digital healthcare research in India since 2017; the majority of publications occurred in 2020 and 2021, with less previous to 2017. Topic modeling of 97 published articles yielded the top three research themes: evaluation, public policy, and communities. The findings from the research themes will provide a thematic understanding of digital healthcare research in India. It will also aid future studies through text analysis, topic modeling, and decision-making in digital healthcare treatments.
Keywords
Digital Healthcare, Topic Modelling, Public Policy, Text Analysis
Cite as
Munikrishnappa Anilkumar, Manasa Nagabhushanam and Mallieswari R, "Topic Modelling of India’s Digital Healthcare Research Trend", In: Mukesh Saraswat and Rajani Kumari (eds), Applied Intelligence and Computing, SCRS, India, 2024, pp. 169-176. https://doi.org/10.56155/978-81-955020-9-7-18