Natural language processing (NLP)

Health Management Glossary

Digital Health and AI

Definition. Natural language processing is the set of computational methods that allow computers to analyse, extract information from and generate human language.

Explanation

NLP ranges from rule-based text mining to statistical models and transformer-based language models. Typical tasks include named entity recognition, classification of documents, extraction of relations and summarisation.

Much clinical information is held as free text in notes, reports and discharge letters. Kreimeyer et al. (2017) show that NLP systems can turn this text into structured data for research, surveillance and quality measurement, but that performance depends on local language, abbreviations and documentation habits, so tools must be validated in the setting where they are used.

Related concepts

Large language models (LLMs) Machine learning Electronic health record (EHR) Artificial intelligence (AI)

Read on The Health Topics

• The Most Popular Research Methods and Analysis Techniques in Management and Organisation Research
• AI’s Role in Modern Drug Regulation
• Large Language Models in Healthcare: A Bibliometric Analysis
• AI in Healthcare: Enhancing Patient Safety Through Risk Management
• Deep Learning for Predictive Maintenance and Health Management
• Evolving Trends in Sentiment Analysis Research

References

Jurafsky, D., & Martin, J. H. (2023). Speech and language processing (3rd ed. draft). Stanford University.

Kreimeyer, K., Foster, M., Pandey, A., Arya, N., Halford, G., Jones, S. F., Forshee, R., Walderhaug, M., & Botsis, T. (2017). Natural language processing systems for capturing and standardizing unstructured clinical information: A systematic review. Journal of Biomedical Informatics, 73, 14–29.

Cite this entry: Kurutkan, M. N. (2026). Natural language processing. In The Health Topics glossary. https://healthtopic.org/glossary/natural-language-processing/

← Back to the glossary