The system design being considered must be able to reach a multitude of users, be lightweight, make use of mobile phones and their cameras. When designing a mobile application in today's society the major consideration must be towards how to make use of the internet. This immediately drove the team to consider a client-server architecture shown below.
The Client would be a mobile app downloaded onto the user's phone that makes use of the phone's camera. The server will be an image processing backend that receives requests from the clients to analyze the image for potential cancer. This seemed like a simple solution. However we know there are common issues when using the public internet infrastructure. Each of the members of the team have worked on modern web applications so we knew this design could have more considerations.
First we knew we would need to make use of modern scalability through the use of cloud services to host the applications backend “server”. Second the design would need to make major security considerations since there would be personal health and identifiable information being stored. This is a major consideration always when designing a system that involves HIPAA regulations. The last area under intense scrutiny was the actual machine learning algorithm being used. The use of artificial intelligence solutions has exploded in recent years due to the computational capabilities catching up. Determining the algorithm that will most likely return the most consistent results is of extreme importance. False negatives could potentially be deadly.
This design led to the systems “server” using microservices. An authentication service to handle user profiles,authentication, authorization and token generation. A service for image processing, which would contain the machine learning algorithm. Finally a communication service that allowed the user to receive feedback from the processing service and for images to be forwarded to medical professionals for further analysis.
