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Healthcare systems still face difficulties in correctly interpreting prescriptions because of unreadable handwriting, linguistic variety, and intricate medical jargon.This paper presents a Multilingual Prescription Image Processing and Medical Analysis Framework that brings together a dual-path Optical Character Recognition (OCR) module with a Tiny LLaMA model that we've fine-tuned using Low-Rank Adaptation (LoRA). What sets our approach apart from traditional OCR systems is that we've woven semantic medical knowledge right into the framework to make it more accessible and understandable across different languages.Our experimental results showed 94.2% OCR accuracy and 91.7% accuracy in medical interpretation, which beat EasyOCR and PaddleOCR by an average of 6.8%. When we tested it across five languages and with different demographic groups, we found an 89% improvement in understanding for non- native speakers and a 76% boost for elderly users. On top of that, the framework provides multilingual text-to-speech functionality and personalized medication reminders to help with adherence and keep patients safe. Overall, our findings demonstrate a scalable and language-inclusive AI approach that strengthens cross-lingual medical communication and supports reliable digital health integration.
Keywords:
OCR, Large Language Models, AI in Healthcare, Multilingual Assessment, Medication Compliance
Cite Article:
"A Multilingual Prescription Recognition and Medical Analysis Framework using OCR and Large Language Model", International Journal for Research Trends and Innovation (www.ijrti.org), ISSN:2456-3315, Vol.11, Issue 5, page no.a495-a499, May-2026, Available :http://www.ijrti.org/papers/IJRTI2605060.pdf
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ISSN:
2456-3315 | IMPACT FACTOR: 8.14 Calculated By Google Scholar| ESTD YEAR: 2016
An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.14 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator