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<journal-meta>
<journal-id journal-id-type="publisher">global-journal-of-computer-science-and-technology-d-neural-ai</journal-id>
<journal-title-group>
<journal-title>Global Journal of Computer Science and Technology - D: Neural &amp; AI</journal-title>
</journal-title-group>
<issn publication-format="print">0975-4350</issn>
<issn publication-format="electronic">0975-4172</issn>
<publisher><publisher-name>Global Journals Publishing Group Incorporated</publisher-name></publisher>
<self-uri xlink:href="https://globaljournals.org/journal-seo-export/jats/117171.xml" />
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<article-meta>
<article-id pub-id-type="publisher-id">117171</article-id>
<title-group>
<article-title>AI-Powered Generative Framework for Automated Clinical Audit Narratives: Regulated Prompt Engineering with LLMs and NLP</article-title>
<subtitle>Automating Clinical Audit Narratives with LLMs</subtitle>
</title-group>
<contrib-group>
<contrib contrib-type="author"><name><surname>Vasanthapuram</surname><given-names>Gangadhar</given-names></name></contrib>
</contrib-group>
<pub-date publication-format="electronic" date-type="pub" iso-8601-date="2025-10-13">
<day>13</day>
<month>10</month>
<year>2025</year>
</pub-date>
<volume>25</volume>
<issue>D1</issue>
<fpage>35</fpage>
<lpage>41</lpage>
<abstract><p>This paper explores an AI-powered framework designed to automate clinical audit narratives, leveraging large language models (LLMs) and natural language processing (NLP). The system employs fine-tuned GPT models, ICD-10-aware embeddings, and regulated prompt engineering to ensure legal compliance. This approach aims to enhance the accuracy, efficiency, and compliance of clinical documentation processes.</p></abstract>
<kwd-group kwd-group-type="author-generated">
<kwd>generative AI</kwd>
<kwd>clinical Aadit</kwd>
<kwd>prompt engineering</kwd>
<kwd>NLP</kwd>
<kwd>automated</kwd>
<kwd>LLM.</kwd>
</kwd-group>
<self-uri content-type="pdf" xlink:href="https://globaljournals.org/GJCST_Volume25/4-AI-Powered.pdf" />
<self-uri content-type="html" xlink:href="https://globaljournals.org/scholarly-articles/ai-powered-generative-framework-for-automated-clinical-audit-narratives-regulated-prompt-engineering-with-llms-and-nlp/" />
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<title>Full Text</title>
<p>This paper explores an AI-powered framework designed to automate clinical audit narratives, leveraging large language models (LLMs) and natural language processing (NLP). The system employs fine-tuned GPT models, ICD-10-aware embeddings, and regulated prompt engineering to ensure legal compliance. This approach aims to enhance the accuracy, efficiency, and compliance of clinical documentation processes.</p>
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