Introduction ⚒

iDoc is a medical assistant app used to diagnose various diseases, suggest medical help, buy online medicines and save your report history. This app works on various types of high level Machine Learning model. The Machine Learning model learns the input image and shows you result. The app consists of an medical bot which helps in identifying various medicines. The app helps to know the top doctors in your area and book an appointment with them. The report section which works on a custom database, saves your appointment reports with all the details. Even if you book a doctor other than from Doctor Bot then also you can add your report physically which will be encrypted and saved in the app. The app provides a MediStore from where you can order your medicines.

Inspiration ❤️

The Idea behind construction of this app was to remove mental pressure of people when they get affected by diseases. During this pandemic when people are not able to visit hospitals frequently they can use this app to identify what diseases are they affected from. The app provides 89.93% accurate result. The app even provides medicinal suggestions according to the symptoms you have. During this high time when people fear to go hospitals, they can have the same guidance and suggestions being at home using Doctor Bot.

We thought to take it to another level by adding a Medi-Store. The Medi-Store is an online medical store from where you can order medicines. In the Medi-Store you don't need to add your prescription or order physically, the doctor who diagnosed you, will add the prescription by himself and the medicine will be delivered to your house. The bot remembers your medicine dosage cycle to expiration such that it would notify you when new medicines are to be ordered as well as the warning notification for expiration of medicine.

So our idea was to create an app which provides 100% guidance and suggestions to a patient regardless of going to the hospital, because during this pandemic going out is more riskier, so we created this app which would take care of your medical related problems by being at home.

How we built it

  • Our app basically consists of 4 main parts:
  • Mobile Application
  • Web Application
  • Backend
  • ML Model

  • Our mobile application is built on Swift language which is compiled using Xcode

  • Our website is built usin HTML5, CSS3, and JavaScript.

  • Our backend is made on Firebase and Nodejs. So we have used firebase for authentication and Custom backend for saving users data.

  • Our ML model is built using CoreML and Swift laguage.

Impact on Society 🌏

This app have a great impact on our society:

  • Reduction in use of carbon films.
  • Secure and safe storage of your report.
  • Less contact between people.
  • Smart Notification to alert dosage timings .
  • Less mental pressure.
  • Reduction in capital spent on hospitals.
  • Record history of diagnostic checkups.
  • Record history of previous reports.

Challenges we faced

  • So initially we needed to figure out how our ML model will work on any image with high accuracy as well as high precision. That took us quite a bit to figure out how we can achieve our desired result.
  • Secondly our ML model accepts image in a format called CVPixelBuffer so we were supposed to convert our jpeg images to CVPixelBuffer and that was a challenging task for us.
  • Then as we considered user privacy to be our foremost priority we were supposed to build a custom backend so that the users data always remains to him and its not shared to any third party server.

Final product

  • Our app and website is fully capable of diagnosing diseases with a high accuracy rate, enable users to book appointments with doctors of their location, organize and access their test history and medical reports using Assistant, buy healthcare products using MediStore and get information like target treatment, side effects and dosage for medicine using MediBot.

Database 🎚

  • The whole app works on Firebase and custom database.
  • For authentication we are using Firebase and to save user reports we have used our custom built backend.
  • The backend is made with MonoDB and Express and written on NodeJS.

Whats Next for i-Doc ?

  • What we are planning is to take i-Doc to the next level by collaborating with Government bodies and including ervery citizens data into i-Doc, so thatevery i-Doc will have data of every citizen and this would help the nation to treat all their citizens in-personal.
  • Other than that we are on a research of how to implement mental disease diagnosis on our app, since right now we ae only focusing on diseases which are visible on you body.
  • We are also planning to add fall detection and various other emergency service on our app.
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