Generative AI for Intelligent Medical Coding and Healthcare Analytics
DOI:
https://doi.org/10.15662/IJARCST.2025.0806027Keywords:
Generative Artificial Intelligence, Intelligent Medical Coding, Healthcare Analytics, Clinical Natural Language Processing, Automated ICD Coding, Electronic Health Records (EHR), Machine Learning in Healthcare, Predictive Healthcare Analytics, Medical Data Automation, AI-Driven Clinical Decision SupportAbstract
Generative AI is emerging as a powerful enabler for intelligent and efficient medical coding to facilitate health data analytics. For predictive analytics, generative models are used alongside conventional classification approaches to predict the onset of diseases, while also serving as an internal validation tool for classifier performance. For risk stratification, generative models enhance the unsupervised stratification of patient populations. Adaptive risk-scoring systems are proposed to identify patients likely to require surgery within the next year, with analysis of state transition paths also possible. Considerations related to the privacy and security of health information in using generative models, and for computer-aided healthcare decision and workflow–support systems in general, are presented. Automated model validation frameworks for supporting ICD and CPT coding systems, along with change management in general, are outlined
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