Natural Language Processing Applications in Medical Data

Authors

Sureh San, Dakota State University
Mark Spanier, Dakota State University

Files

Description

Natural Language Processing (NLP) is the utilization of Artificial Intelligence / Machine Learning in understanding human language. NLP is increasingly being applied in the realm of healthcare as it can make information processing highly efficient through data summarization. In this modern day of technology, data is increasing at an unprecedented pace, and AI can assist in organizing unstructured information. In this use case, Named Entity Recognition, which is the classification of words, can recognize key terms in medical information. This study provides in depth research on the foundations of Natural Language Processing for healthcare use cases. Furthermore, comparison of AI models were put in place to apply information gained in order to see which models are most effective in Named Entity Recognition for the purpose of healthcare term. Specifically, open-source models like BERT and SpaCy were fine-tuned to process medical texts. In some cases, synthesized data was created to generate more results in a controlled environment.

Publication Date

2025

Recommended Citation

San, Sureh and Spanier, Mark, "Natural Language Processing Applications in Medical Data" (2025). Annual Research Symposium. 60.
https://scholar.dsu.edu/research-symposium/60