A Novel Approach for Biomedical Text Classification Using Deep Learning and NLP for Disease Prediction

Authors

  • Greeshma G. S. Assistant Professor, Department of Computer science and Engineering
  • Bindiya Ahuja Professor, Department CSE, Lingaya’s Vidyapeeth
  • Harshita Samota Assistant professor, panipat institute of engineering and technology, Samalkha, Haryana, India
  • K. Vanitha Associate Professor, Department of Computer Science and Engineering, Faculty of Engineering, Karpagam Academy of Higher Education(Deemed to be University) Coimbatore, India
  • Alok Dubey Associate professor, Department of Preventive Dental Sciences, College of Dentistry, Jazan University, Jazan, Saudi Arabia.
  • Sheetal Mujoo Assistant professor, Department of Maxillofacial Surgery and Diagnostic Sciences, College of Dentistry, Jazan University, Jazan, Saudi Arabia.
  • Saneesh P. S. Former Assistant Professor, Department: Computer Science and Engineering, Sreepathy Institute of Management and Technology, Kerala

Keywords:

Biomedical text classification, Deep learning, NLP, Disease prediction

Abstract

Biomedical text classification is crucial for automating the analysis of vast biomedical literature to aid in disease prediction, given the exponential growth of biomedical data. Integrating deep learning methods with natural language processing (NLP) has revolutionized this field, offering unprecedented capabilities in understanding and extracting intricate patterns from text data coupled with advanced NLP techniques, enable researchers to uncover hidden associations between biomedical concepts, identify novel biomarkers, and enhance disease prediction accuracy. In this study, we investigate the application of deep learning and NLP for biomedical text classification, presenting a novel framework that harnesses deep neural networks to capture semantic relationships and domain-specific knowledge. Through extensive experimentation on benchmark datasets, we demonstrate the effectiveness of our approach compared to traditional machine learning methods. Our research contributes to advancing biomedical text classification, highlighting the transformative potential of deep learning and NLP in healthcare research and practice.

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References

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Published

24.03.2024

How to Cite

G. S., G. ., Ahuja, B. ., Samota, H. ., Vanitha, K. ., Dubey, A. ., Mujoo, S. ., & P. S., S. . (2024). A Novel Approach for Biomedical Text Classification Using Deep Learning and NLP for Disease Prediction. International Journal of Intelligent Systems and Applications in Engineering, 12(20s), 657–666. Retrieved from https://ijisae.org/index.php/IJISAE/article/view/5196

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Section

Research Article

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