Benign Health



Technologies Used

Front End - React, SCSS

Design - Adobe XD

Backend - Python3 Rest API with Apache2, Gunicorn and Flask

Hosting - AWS EC2

BenignHealth- AI Research Tool for Cancer Diagnosis

BenignHealth is an AI-powered research study aimed at generating a dedicated algorithm for accuracy determination of breast cancer mammographic results.

About BenignHealth

BenignHealth is essentially a research study using an AI tool for a medical experiment. The prime aim of this study is to generate AI algorithms that can facilitate accurate analysis of mammographic results for breast cancer. Ultimately, the study also seeks to extend benefits to radiology for boosting the accuracy rate of a cancer diagnosis. BenignHealth targets the fallacies of even the most advanced radiology devices that lead to reporting errors and false diagnoses. The tool collects data from the surveys, processes it, and assimilates it towards algorithm production.

As BenignHealth was a novel project for us, we aimed at taking utmost care to make its purpose and functioning seem subtler to the survey takers. Following were the major components of this project that we developed:

  • A web application for the research surveys
  • A mobile application for the research surveys
  • A questionnaire for the survey
  • An algorithm for result generation from the surveys

Key Milestones of the Project

It was a relatively simple project but demanded high precision of the efforts being put in. We developed and implemented the following parts of the project.

Web Platform

We developed a web application for BenignHealth to convey the research details and allow users to take the survey. It is a single-page website which we designed meticulously. We kept the scheme relatively simpler with a focus on making the UI attractive. An attractive color plan was used with the hamburger menu in the center to make navigation easy.

Mobile Application

We also developed a mobile application for BenignHealth to allow easy access to the survey to the users. The mobile application is compatible with both iOS and Android as it is built with the React Native framework. Other than the basic information about the research, the users can also access the questionnaire on the app.

AI Tool for Data Processing

This is the most crucial part of the BenignHealth research. The data collected from the survey taken by individual users are processed towards result generation. We developed an AI-powered tool for this purpose including a particular algorithm. This algorithm was built with Python and Flask technologies. Whatever data or values are passed through the tool, it processes it for instant result generation as well as stores for research purposes.

Questionnaire for the Survey

We prepared a questionnaire for the users that seek data from their mammography results and personal health status. It’s a set of questions that the users have to answer by putting in a value. The data, thereby, collected from the questionnaire is processed followed by result generation on mammography report accuracy.

Project Management

This project was very important due to its novel aim and we wanted to implement it flawlessly. Task management was carried out through Jira software for agile projects and issue tracking. Slack was used for effective and collaborative team communications. We also used Asana along with Jira for testing and issue reporting.

Final Results

BenignHealth is a path-breaking endeavor that will be contributing significantly to the field of radiology if proven successful. This research tool is going to benefit a plethora of users by assisting their medical health status. The comprehensive questionnaire and AI tool coordinate together towards testing the accuracy of mammographic reports.

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