Routing images of medical tests

Description: convenient storage and use of information obtained from medical analyses of clients of the telemedicine mobile app implies a friendly process of downloading and digitizing paper medical analyses. Automation of loading and systematization of medical analysis sets of the mobile platform user uses modern methods of detecting and classifying images for their subsequent processing.

Context: for users of a mobile medical app, you need to implement a model that allows the user to upload an image and automatically tag it.

Decision: created a model based on OCR and the language recognition model.

Results:
The solution is integrated into the customer's business process:

Reducing the load on specialists by 60%;
Increase the speed of document processing in the business process by 10%;
Reduced costs due to lost documents by 5%.

Built solutions for automatic speech recognition:

Receipts;
Invoices;
Order-out;
Contract agreement.

To build the model, we used:

Set of categories of medical tests;
Database of images of medical tests;
The marking of images by category.

Simulation result:
Model for classifying images by category.

Customer: Medicine, Telecom

Technology stack: OCR, TensorFlow, nltk, Python.