Context-Aware NLP in Healthcare: AI-Powered Medical Text Processing for Clinical Decision Support Systems

The rapid advancement of Natural Language Processing (NLP) and Artificial Intelligence (AI) has created substantial opportunities for improving healthcare delivery, particularly in the realm of clinical decision support systems (CDSS). Context-aware NLP techniques are increasingly being integrated into healthcare settings to extract valuable insights from unstructured medical texts. The role of Software Engineering in building scalable and efficient AI-driven healthcare solutions is paramount, especially in handling APIs, Distributed Systems, and Image Processing for seamless data integration. This paper explores the intersection of AI-driven NLP and healthcare, with a focus on developing context-aware solutions to enhance clinical decision-making. It reviews existing methodologies, challenges, and future directions for improving the accuracy, efficiency, and usability of these systems, with implications for patient outcomes and healthcare providers.

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-03-04
DOI
https://doi.org/10.5281/zenodo.14964401
Primary Topic
Artificial Intelligence in Healthcare and Education
Type
article
Field-Weighted Citation Impact
0.00
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article

Context-Aware NLP in Healthcare: AI-Powered Medical Text Processing for Clinical Decision Support Systems

Zenodo (CERN European Organization for Nuclear Research)
Artificial Intelligence in Healthcare and Education
article

Context-Aware NLP in Healthcare: AI-Powered Medical Text Processing for Clinical Decision Support Systems

article en

Abstract

The rapid advancement of Natural Language Processing (NLP) and Artificial Intelligence (AI) has created substantial opportunities for improving healthcare delivery, particularly in the realm of clinical decision support systems (CDSS). Context-aware NLP techniques are increasingly being integrated into healthcare settings to extract valuable insights from unstructured medical texts. The role of Software Engineering in building scalable and efficient AI-driven healthcare solutions is paramount, especially in handling APIs, Distributed Systems, and Image Processing for seamless data integration. This paper explores the intersection of AI-driven NLP and healthcare, with a focus on developing context-aware solutions to enhance clinical decision-making. It reviews existing methodologies, challenges, and future directions for improving the accuracy, efficiency, and usability of these systems, with implications for patient outcomes and healthcare providers.

Zenodo (CERN European Organization for Nuclear Research)
Higher Education Commission (PK), Software Research Associates (Japan) (JP), Guardian Life Insurance Company of America (United States) (US)
Openalex Percentile: Top 57%
Artificial Intelligence in Healthcare and Education
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Context-Aware NLP in Healthcare: AI-Powered Medical Text Processing for Clinical Decision Support Systems · Zenodo (CERN European Organization for Nuclear Research) (2025) | TGRS Research Map | TGRS