Nlc Icd10 Classifier
A simple web app that shows how Watson's Natural Language Classifier (NLC) can classify ICD-10 code. The app is written in Python using the Flask framework and leverages the Watson Developer Cloud Python SDK
Overview:
This document introduces an application built to demonstrate IBM's Watson Natural Language Classifier (NLC) for medical diagnosis classification with ICD-10 codes. It explains the purpose of the application, the data set used, and how it can help hospitals and insurance companies in tagging accurate ICD-10 codes. The application is a Python web app based on the Flask microframework.
Features:
- Classification with ICD-10 Code: Utilizes IBM's Watson NLC to classify medical diagnoses with ICD-10 codes.
- Training with CSV Data: Trains the NLC model using a subset of ICD-10 entries from a provided CSV file.
- Flask Web App: Deploys a web app using Flask framework for easy querying of the NLC model.
- Integration with ICD-10 API: Utilizes the freely available ICD-10 API to retrieve names and descriptions based on ICD-10 codes.
- Easy Deployment: Provides a step-by-step guide for creating NLC service, training model, and running the web application.
Summary:
The application is designed to showcase the capabilities of IBM's Watson NLC in classifying medical diagnoses using ICD-10 codes. It leverages a Python web app built on Flask framework and provides a seamless integration with the ICD-10 API for accurate tagging of diseases and health issues. With step-by-step instructions for setting up the NLC service, training the model, and deploying the web app, users can easily understand and implement the classification process.