When medical prescriptions are written in difficult-to-read handwriting patients face greater danger of medication errors alongside interrupted healthcare operations and compromised safety. An OCR-NLP-based approach within our project serves to both accurately interpret and validate handwritten medical prescriptions precisely. The system implements advanced language models to achieve precise interpretation while it reduces the chance of medication errors between healthcare providers and pharmacists. The friendly interface gives patients complete drug information access which supports their pharmacy operations to produce streamlined workflows that boost efficiency rates. This innovative technology minimizes human errors through its automated text recognition and system-driven processes to create safer prescriptions while delivering improved healthcare outcomes. "Our OCR-NLP based solution revolutionizes prescription management by accurately interpreting handwritten prescriptions, minimizing medication errors, enhancing patient safety, and streamlining pharmacy workflows."
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About the Entrant
- Name:Murali G
- Type of entry:teamTeam members:
- KARTHICK RAJ R
- AADHISH KUMARAN P
- Software used for this entry:Google Colab
- Patent status:none