This dataset is originally from UCI Machine Learning Repository. It contains the sign and symptom data of newly diabetic or would be diabetic patient. This has been col- lected using direct questionnaires from the patients of Sylhet Diabetes Hospital in Sylhet, Bangladesh and approved by a doctor.
- Age 1.20-65
- Sex 1. Male, 2.Female
- Polyuria 1.Yes, 2.No.
- Polydipsia 1.Yes, 2.No.
- sudden weight loss 1.Yes, 2.No.
- weakness 1.Yes, 2.No.
- Polyphagia 1.Yes, 2.No.
- Genital thrush 1.Yes, 2.No.
- visual blurring 1.Yes, 2.No.
- Itching 1.Yes, 2.No.
- Irritability 1.Yes, 2.No.
- delayed healing 1.Yes, 2.No.
- partial paresis 1.Yes, 2.No.
- muscle stiffness 1.Yes, 2.No.
- Alopecia 1.Yes, 2.No.
- Obesity 1.Yes, 2.No.
- Class 1.Positive, 2.Negative.
Dockers are used to run the application. To run the application, you need to install docker. Then, you can run the application with the following command:
docker build -t <image-name> .
docker run -p 8000:8000 -v models:/app/models <image-name>
The application exposes the following APIs:
- POST /predict
- URL: http://localhost:8000/predict
- Body Request
{
"age": 30,
"gender": "Male",
"polyuria": 1,
"polydipsia": 0,
"sudden_weight_loss": 1,
"weakness": 0,
"polyphagia": 1,
"genital_thrush": 0,
"visual_blurring": 1,
"itching": 0,
"irritability": 1,
"delayed_healing": 0,
"partial_paresis": 1,
"muscle_stiffness": 0,
"alopecia": 1
}
- Response
{
"message": "It is predicted that this patient has diabetes.",
"status": 1
}
@TODO add more information about the models, the training process, and the results.