Yann-dv / MediScreenApp

Diabetes Prediction Project

Table of Contents

• Project Overview
• Project Objectives
• Key Features
• Project Structure
• Deliverables
• Technical Details
  • Technologies Used
  • System Architecture
  • Sprint 1
    • Tasks
    • REST Service
    • Docker Infrastructure
  • Sprint 2
    • Tasks
    • Report Generation
  • Sprint 3
    • Tasks
    • Integration
• Conclusion

Project Overview

The Diabetes Prediction Project is a comprehensive initiative to develop a diabetes prediction system for our client. This system leverages microservices and a RESTful architecture to facilitate diabetes prediction based on patient data and medical history.

Project Objectives

The primary objectives of this project are as follows:

• Design and implement a robust Docker infrastructure for microservices.
• Create a RESTful service for accessing patient records.
• Develop a system for generating diabetes reports.
• Utilize .NET Core MVC as the primary framework for development.

Key Features

1. Docker Infrastructure: The project involves setting up an efficient Docker infrastructure that allows for easy deployment and scaling of microservices. The Docker infrastructure also ensures a consistent runtime environment across different stages of the project. The project is configured to be containerized on the linux docker. This requires WSL2 installed for Windows machines, as well as docker desktop to facilitate management
2. RESTful Service: We create a RESTful API for seamless access to patient records, ensuring data availability for analysis.
3. Diabetes Report Generation: At the heart of the project is the ability to generate diabetes reports, aiding in medical decision-making.

Project Structure

The project is organized into three sprints, each serving a specific purpose:

• Sprint 1: Focuses on laying the foundation for the project, including Docker infrastructure setup and the creation of a REST service.
• Sprint 2: Concentrates on additional feature development, especially the mechanism for generating diabetes reports.
• Sprint 3: Wraps up the project by integrating all microservices and finalizing the diabetes prediction system.

Deliverables

The deliverables for this project are crucial to tracking progress and ensuring that the objectives are met. They include:

1. Kanban Board: A link to the updated Kanban board, which provides a visual representation of project tasks and progress.
2. Retropective Templates: Completed retrospective templates for each sprint, capturing insights and lessons learned.
3. Code Project Archive: A Zip archive of the project's code, including a link to the GitHub repository where the code is hosted. This also includes a test report and Docker configuration files.
4. REST Service Documentation: Comprehensive documentation outlining the REST services created, including API endpoints, request/response formats, and data models :
   • PDF Swagger Documentation
   • JSON Swagger Documentation

Technical Details

Technologies Used

• .NET Core MVC: Chosen as the core framework for its versatility and compatibility with microservices.
• Docker: Facilitating containerization and deployment.
• RESTful API: Enabling data access and interaction.
• Swagger: Used for API documentation.
• SQL Database: Utilized for patient data storage.
• MongoDb Database: Utilized for doctor's notes data storage.

System Architecture

The project architecture follows a microservices-based approach, enabling modular development, easy scalability, and efficient resource utilization. Each microservice is encapsulated within a Docker container to ensure portability and flexibility in deployment.

Sprint 1

Tasks

Sprint 1 focuses on essential groundwork and infrastructure development:

• Docker environment setup.
• REST service for patient data access.

REST Service

The REST service provides access to patient records and is designed around the principles of RESTful architecture. It offers endpoints for data retrieval and modification.

Docker Infrastructure

The Docker infrastructure streamlines the deployment of microservices and ensures a consistent runtime environment across different stages of the project.

Sprint 2

Tasks

Sprint 2 involves the development of the report generation feature, expanding the project's functionality.

Report Generation

Report generation is a critical component of the project, allowing healthcare professionals to analyze patient data and make informed decisions. This feature compiles patient information and produces comprehensive diabetes reports.

Sprint 3

Tasks

Sprint 3 finalizes the project with integration and testing of all microservices.

Integration

This sprint involves the integration of all microservices to ensure that they work cohesively, contributing to the overall goal of diabetes prediction.

Test report

The test report is a comprehensive document that outlines the testing process and results. It includes a summary of the testing approach, test cases, and test results.

Conclusion

The Diabetes Prediction Project represents a significant step toward enhancing medical decision-making through technology. By leveraging microservices, Docker, and RESTful architecture, we have developed a versatile system that can contribute to the prediction of diabetes based on patient data. This README serves as both documentation and a guide for stakeholders, providing insight into the project's objectives, structure, and technical aspects.