From Scribbles to Structured Data: Processing Handwritten Prescriptions with Spark NLP
Introduction Medical prescriptions, often scribbled in hurried handwriting, pose a significant challenge when attempting to extract valuable information. Automating this process requires a robust combination of Optical Character Recognition (OCR) and Natural Language Processing (NLP) tools to accurately identify entities like medication names, dosages, and medical conditions. In this article, we delve into a Spark NLP-based pipeline to convert handwritten prescriptions into structured, machine-readable text. Leveraging BERT embeddings for contextual understanding and a custom Named Entity Recognition(NER) model, this approach promises to streamline information extraction in medical workflows....