Text Mining and Network Visualization on Biomedical Literature

DOI

10.2991/978-94-6239-756-9_19How to use a DOI?

Keywords

Biomedical; Text mining; Network visualization; Cytoscape

Abstract

The availability of enormous research articles in the biomedical field makes highlighting significant research in the field of interest difficult. Text mining helps identify data of importance from a vast pool of data, while network visualization gives a graphical presentation of the data for easy understanding. Text Mining of Biomedical literature helps build biological networks between the data. The proposed work presents an approach for text mining biomedical literature to build a network between the data using Cytoscape. It uses text mining techniques like Tokenization, Lemmatization, and Stop.

Copyright

© 2026 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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TY  - CONF
AU  - Sonali Kothari
AU  - Karan Desai
AU  - Vijayshri Khedkar
AU  - Ujwala Kshirsagar
AU  - Uday Patkar
PY  - 2026
DA  - 2026/08/31
TI  - Text Mining and Network Visualization on Biomedical Literature
BT  - Proceedings of the Conference on Bioengineering for Global Health (SYMRESEARCH 2.0 2025)
PB  - Atlantis Press
SP  - 271
EP  - 281
SN  - 2468-5747
UR  - https://doi.org/10.2991/978-94-6239-756-9_19
DO  - 10.2991/978-94-6239-756-9_19
ID  - Kothari2026
ER  -