Clinical Entity Recognition and Longitudinal Patient Summary Generation: AI-Driven Natural Language Processing Systems for Automated Medical Record Analysis

Authors

  • Stefan Wagner Associate Professor of Computer Science, Graz University of Technology

Keywords:

clinical entity recognition, longitudinal patient summary generation, natural language processing systems, automated medical record analysis, machine learning

Abstract

Artificial intelligence (AI) is increasingly playing a transformative role in the healthcare sector. In addition to many other possibilities, one of the first considerations is its opportunity to boost diagnostic accuracy and quicker, more informed decisions by care providers, allowing for significant advancements in resource use and patient care. In terms of hard data, the efficiency and resources of healthcare forecasting are significantly threatened.

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Published

31-12-2021

How to Cite

[1]
“Clinical Entity Recognition and Longitudinal Patient Summary Generation: AI-Driven Natural Language Processing Systems for Automated Medical Record Analysis”, IoT and Edge Comp. J, vol. 1, no. 2, pp. 38–48, Dec. 2021, Accessed: Jun. 05, 2026. [Online]. Available: https://thesciencebrigade.com/iotecj/article/view/738