/DotComDoctor-SoftwareEngineeringProject

DotComDoctor is an AI-ML Based Disease Prediction Chatbot made by Jaideep Singh, Nikhil Shaji Kunnathu and Nishant Puri as a part of our Software Engineering, Artificial Intelligence and Web Technologies courses

Primary LanguageHTML

DotComDoctor

An AI Based Disease Prediction ChatBot


Team Members:
Jaideep Singh: 18103005
Nishant Puri: 18103019
Nikhil Shaji Kunnathu: 18103109


This Project has been created as a part of our
Artificial Intelligence (CSN-305),
Software Engineering (CSN-302),
Web Technologies (CSN-303)
Courses for the Academic Semester 202021


Note: We have followed an Agile approach (Kanban Method to be precise), and have conducted our sprints using Trello Boards

Here is the link to VIEW our Trello Board: DotComDoctor-Kanban Board


Screenshots:

To Be Added.


Usage:

To Be Added.


Timeline :

28 July, 2020 - 21 August, 2020:
Team Formation, Planning, and Project Finalisation

  • We formed our 3 member Team for the Project
  • We deliberated on various paradigms of AI that could be incorporated on a Web-Based Platform
  • We came up with the idea of an AI Based ChatBot which could serve as some kind of Virtual Doctor
  • Thus, we finalised our Project Summary

22 August, 2020 - 21 September, 2020:
Learning Phase I and Development Phase I

  • Navigated through various Tech-Stacks
  • Finalised as such:
    • Website Front-End: HTML, CSS, JavaScript
    • Website Hosting(Back-End): Flask, Heroku
    • Machine Learning: Decision Tree Classifier, Natural Language Processing
  • To achieve this Tech-Stack, we had to focus on a Learning Phase for these Technologies which proceeded through the given time
  • At the end of this period we delivered the UML Class and UseCase Diagrams

21 September, 2020 - 30 September, 2020:
Learning Phase II

  • Our main focus of this phase was to consolidate our Learnings and create a Planned Approach for our Project
  • By the end of this phase we rejected some ideas (As shown in the Trello Board) and improved upon other ideas
  • At the end of this period we delivered the UML Sequence, Activity, and State Chart Diagrams

1 October, 2020 - 15 October, 2020:
Learning Phase III and Development Phase II

  • After consolidating our learnings from the previous phase, we noe started developing our Website
  • We used 2 Machine Learning Models (Decision Tree Classifier and Random Forest Classifier) for classifying the diseases based on symptoms
  • We created a Simple Flask Server for testing the Pickle Files
  • Then we picked up NLP and Deep Learning(An Added Idea in Phase 2) to add o our Tech Stack

16 October, 2020 - 6 November, 2020:
Development Phase III

  • Completed Basics of Learning and Using Maps API
  • Solved Error of using multiple Features and Labels at once
  • System (without NLP Model) is Complete now for Five Diseases, namely Dengue, Common Cold, Chicken Pox, Tuberculosis, Jaundice

7 November, 2020 - 19 November, 2020
Development Phase IV

  • We are completed the Maps API with routes
  • Using NLP to make the symptoms less scattered
  • Working on our final presentation (including Look and Feel of the Final Web App)

The Project is now complete