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Extract text from scanned documents
Medical Ner App

Medical Ner App

Extract named entities from medical text

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What is Medical Ner App ?

Medical Ner App is a specialized tool designed to extract named entities from medical text. It helps users identify and categorize specific information such as diagnoses, medications, symptoms, and medical terms from scanned documents. This app is particularly useful for healthcare professionals, researchers, and anyone needing to process medical data efficiently.

Features

• Named Entity Recognition (NER): Automatically identifies and categorizes medical entities in text.
• Support for Scanned Documents: Utilizes OCR (Optical Character Recognition) to extract text from scanned medical documents.
• High Accuracy: Designed to handle complex medical terminology and contexts.
• User-Friendly Interface: Easy-to-use platform for uploading documents and viewing results.
• Customizable Extraction: Allows users to define specific entities they want to extract.

How to use Medical Ner App ?

  1. Upload or Select Document: Import your scanned medical document into the app.
  2. Apply OCR (if needed): If the document is scanned, use the OCR feature to extract readable text.
  3. Select Entity Types: Choose the types of entities you want to extract (e.g., diagnoses, medications, symptoms).
  4. Process the Document: Run the extraction process to identify and categorize the entities.
  5. View and Export Results: Review the extracted information and export it for further use.

Frequently Asked Questions

1. What file formats does Medical Ner App support?
Medical Ner App supports common formats like PDF, JPG, PNG, and TIFF for scanned documents.

2. How long does the extraction process take?
Processing time depends on the document length and complexity. Scanned documents may take longer due to OCR processing.

3. Can the app handle handwritten medical notes?
While the app primarily works with typed or clearly scanned text, it may struggle with handwritten notes unless they are very legible. For best results, use clear, typed, or high-quality scanned documents.

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