Made by Subhadeep Kundu, Alapan Kar, Sukrit Bhattacharya, Anuvab Biswas
Doctogram- a smart disease prediction app built using ML that predicts disease based on the symptoms given by user.
These days there are too many tools for “Disease Prediction”. But the apps mainly focus on the heart diseases that have been analyzed. But there are no apps that are used for the prediction of general diseases. Moreover, if there are such applications which do predict diseases, the accuracy factor is still not up to the mark. So Doctogram does successful analysis by generating meaningful patterns from structured and unstructured data from the information presented by the patients and helps for the prediction of the general diseases absolutely free of cost.
The general objective is to develop a web interface platform to predict the occurrences of various diseases on the basis of various symptoms. The user can select the various symptoms and can find the probable disease which they are suffering from. Doctogram is equipped with the following features: a. After prediction of the disease it would show more articles about the disease from authoritative sources. b. Doctogram does not prescribe any kind of medication and is only meant for giving the user a probable disease that he might be suffering from based on his Symptoms. c. Doctogram would provide information about nearest health care units which provides treatment for the disease.
We have made use of two classifying algorithms- Random Forest Classification and Decision Tree Classification.As input,symptoms are provided for the model.Based on the symptoms input, the disease is predicted. A hyperlink is generated with a link to that particular disease so that the user can read up more about it. Another feature is the option of looking up Hospitals within a 4km radius from your current location to make an appointment and get checkup up with ease at the earliest.
In Git Bash
git clone https://github.com/mozohack/Bots_With_Dots.gitOpen the cloned GitHub repository folder and open CMD in it.
pip install flask
python xy.py After this the server is up and running.
In the browser open the path containing the index.php file.