Oncolens Detect: Empowering Early Cancer Detection
Project Description
An innovative web application designed to revolutionize early cancer detection. Leveraging advanced technologies, CancerTrack provides a comprehensive platform for screening, diagnosing, and monitoring cancer in its earliest stages. With a user-friendly interface and powerful diagnostic tools, CancerTrack empowers healthcare professionals and patients alike to detect cancer early, leading to better treatment outcomes and improved survival rates.
Role and Contributions
- Designed the Overall Architecture: Took charge of designing the architecture of the Healthcare Management System, ensuring scalability, maintainability, and adherence to best practices.
- Developed Django Backend Models and RESTful APIs: Spearheaded the development of Django backend models, meticulously crafting data entities such as patients, test results, diagnoses, and treatments.
- Implemented Frontend Components with React and Redux: Led the implementation of frontend components using React and Redux, focusing on creating intuitive user interfaces for efficient data entry and management.
- Configured OAuth with Google for User Authentication: Implemented OAuth with Google to ensure secure user authentication, leveraging industry-standard protocols to protect sensitive data and provide seamless login experiences.
- Designed and Created the Database Schema: Designed and created a robust database schema based on Django models, ensuring data integrity and efficient data retrieval.
- Wrote End-to-End Tests with Selenium: Developed comprehensive end-to-end tests using Selenium, meticulously crafting test cases to simulate user interactions and validate application functionality, thereby ensuring a reliable user experience.
- Defined Infrastructure Requirements using Terraform: Defined infrastructure requirements using Terraform, meticulously planning and provisioning resources such as virtual machines, databases, and networking components, paving the way for seamless deployment and scalability.
- Containerized Applications with Docker and Deployed to Kubernetes: Led the containerization efforts, Dockerizing both the Django backend and React frontend applications. Deployed containers to a Kubernetes cluster, ensuring efficient orchestration and scalability.
- Set Up CI/CD Pipelines using Buildkite for Automated Deployment: Established CI/CD pipelines using Buildkite, automating the build, test, and deployment processes.
Outcomes and Results
- A Robust and Efficient Web Application: The Healthcare Management System emerged as a robust and efficient web application, meticulously designed to streamline patient data management for healthcare providers.
- Enhanced Patient Data Management: By providing a centralized platform for managing patient information, including test results, diagnoses, and treatments, the Healthcare Management System has revolutionized patient data management practices.
- Improved Decision-Making through Data Insights: Leveraging advanced data analytics capabilities embedded within the system, healthcare professionals can derive valuable insights from patient data.
Technologies Used
- Backend Development with Django: Created Django models to represent entities such as patients, test results, diagnoses, and treatments.
- Frontend Development with React and Redux: Set up a React project structure with Redux for state management.
- Database Management with MySQL or SQLite: Designed and created the database schema based on Django models.
- Testing with Selenium: Wrote end-to-end tests using Selenium to ensure application functionality.
- Infrastructure as Code (IaC) with Terraform: Defined infrastructure requirements using Terraform for deployment.
- Containerization and Orchestration with Docker and Kubernetes: Containerized the Django backend and React frontend using Docker.
- Continuous Integration and Continuous Deployment (CI/CD) with Buildkite: Set up CI/CD pipelines with Buildkite for automated build, test, and deployment processes.
Challenges Faced and Solutions
- Challenge: One of the primary challenges encountered was designing a data model capable of handling the complex and evolving nature of patient data in healthcare environments.
Solution: Leveraging the capabilities of SQLAlchemy, the data model was meticulously crafted to establish clear relationships between database entities. - Challenge: Ensuring the security of sensitive patient data presented a critical challenge.
Solution: Secure authentication mechanisms were implemented using Flask-Security and JWT (JSON Web Tokens), encrypting sensitive data and enforcing access controls.