Disease Prediction System

Disease Prediction will be the platform where a user can get prediction of disease by providing symptoms. By providing these symptoms our platform will indicate which type of disease user can have based on their symptoms. The predicted result (disease name) will be based on the prediction model that

Project Title

Disease Prediction System

Project Area of Specialization

Artificial Intelligence

Project Summary

Disease Prediction will be the platform where a user can get prediction of disease by providing symptoms. By providing these symptoms our platform will indicate which type of disease user can have based on their symptoms. The predicted result (disease name) will be based on the prediction model that will be made by deploying ML algorithms on dataset. The user will no longer have to face the difficulty of visiting doctors and taking appointments for even a minor symptom instead they can just add their symptoms in our system to see the results of accuracy percentage if they really need to visit a doctor or they are actually suffering from a disease according to their health condition from the accuracy.

Project Objectives

The project will help user identify his/her disease before going through the expensive process of medical tests or treatments. What our project is benefiting is an ease to the users to identify the disease and take the prescription according to the detection. This project will help us predicting the patient’s health accuracy based on the symptoms he added and calculating results by machine learning algorithms.

• We will deploy machine learning algorithm like RF, DT, KNN etc.
• We will get the dataset through Kaggle or google search engine.
• Disease Prediction
• Medicines Suggestion
• Doctors Suggestion
• Ease to the users

Project Implementation Method

We have planned to divide the project into 5 phases. For FYP – 1 functional features/ deliverables will be:

• Dataset Collection
  • Dataset Cleaning
• Deployment of ML algorithms
  • Without Hyper Parameter Tuning
  • With Hyper Parameter Tuning
  • Selection of one algorithm for creation of prediction model on the basis of best accuracy score

Comparison of Classification Report

For FYP – 2 functional features/ deliverables will be:

• Model Creation
  • Testing of model through API
• Development of front end (web portal)
  • Model testing on the front end

Integration of Database in order to collect more data.

Benefits of the Project

The main purpose of this online disease prediction system is to save the precious time and cost from visiting the hospitals for even a minor symptom and we will get the diagnostics in our hands on the basis of entered symptoms that will lead us weather we should visit the doctor for these minor symptoms or the disease leads to some major problems or not also the prescription and the list of doctors will help the patient to choose whom he should choose for consultation.

This online disease prediction system will suggest you the list of doctors whom you can visit on the basis of your diagnostics related to that disease i.e., the expertise of that area of a particular disease whom you can put your trust on without wasting your time finding one for you whom you should visit. This system will also show you prescription also on the basis of diagnosed disease.

Technical Details of Final Deliverable

We are using Machine Learning technique to train the dataset and then apply testing through different parametarized methods and select one algorithm on the basis of the best accuracy score and then we will create the prediction model by using PICKLE, and API through postman software. furthermore MySQL will be used for the storage of more data.

Final Deliverable of the Project

Software System

Core Industry

Health

Other Industries

IT

Core Technology

Artificial Intelligence(AI)

Other Technologies

Sustainable Development Goals

Good Health and Well-Being for People, Industry, Innovation and Infrastructure

Required Resources

If you need this project, please contact me on contact@adikhanofficial.com