Biomedical Text Mining - Applications and Challenges: Studying applications and challenges of biomedical text mining for extracting and analyzing information from scientific literature and medical records
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Keywords

Biomedical text mining
applications
challenges

How to Cite

[1]
Dr. Beatrice Kern, “Biomedical Text Mining - Applications and Challenges: Studying applications and challenges of biomedical text mining for extracting and analyzing information from scientific literature and medical records”, Journal of Bioinformatics and Artificial Intelligence, vol. 1, no. 1, pp. 21–29, Jun. 2024, Accessed: Nov. 25, 2024. [Online]. Available: https://biotechjournal.org/index.php/jbai/article/view/24

Abstract

Biomedical text mining (BTM) has emerged as a powerful tool in biomedical research, offering the ability to extract and analyze vast amounts of information from scientific literature and medical records. This paper provides an overview of the applications and challenges of BTM, highlighting its role in advancing biomedical research and healthcare. We discuss various applications of BTM, including information retrieval, information extraction, and knowledge discovery. Additionally, we explore the challenges associated with BTM, such as data complexity, domain specificity, and ethical considerations. By addressing these challenges, BTM has the potential to revolutionize biomedical research and improve patient care.

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References

Mahammad Shaik, et al. “Unveiling the Achilles’ Heel of Decentralized Identity: A Comprehensive Exploration of Scalability and Performance Bottlenecks in Blockchain-Based Identity Management Systems”. Distributed Learning and Broad Applications in Scientific Research, vol. 5, June 2019, pp. 1-22, https://dlabi.org/index.php/journal/article/view/3.

Tatineni, Sumanth. "Enhancing Fraud Detection in Financial Transactions using Machine Learning and Blockchain." International Journal of Information Technology and Management Information Systems (IJITMIS) 11.1 (2020): 8-15.

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