pneumonia-diagnosis.md

VGG19 Pneumonia Diagnosis

This service uses VGG19 to detect whether patients have pneumonia, both bacterial and viral, based on an X-ray image of their chest.

This service is based on Alishba Imran's work.

It is part of our third party DNN Model Services.

Welcome

The service receives an X-ray chest image and uses it as an input for a pre-trained VGG19 model.

The model was trained using this Kaggle's dataset, and has achieved an accuracy of 77,52%.

What’s the point?

The service makes prediction using computer vision and machine learning techniques.

The service outputs "Pneumonia" for images that has a probability to have pneumonia or "Normal" otherwise.

How does it work?

The user must provide the following inputs in order to start the service and get a response:

Inputs:

• gRPC method: check.
• img_path: An X-ray chest image URL.

You can use this service from SingularityNET DApp.

You can also call the service from SingularityNET CLI (snet).

Assuming that you have an open channel to this service:

$ snet client call snet pneumonia-diagnosis default_group check '{"img_path": "https://snet-models.s3.amazonaws.com/bh/PneumoniaDiagnosis/diagnosis_normal_2.jpg"}'
...
Read call params from cmdline...

Calling service...

    response:
        output: "Normal"

What to expect from this service?

Input image:

Response:

output: "Normal"

Input image:

Response:

output: "Pneumonia"