As we recognized from professionals in the healthcare field, one of the main constant complaints they have is about unintuitive and unattractive, electronic health record systems. These software packages can also can be bulky to use and provide limited capabilities.
Our software aims to solve that issue by providing a clean and easy to use user interface, that is updated to the current standards of webpages. We also recognized the need to implement searching and aggregation capabilities through a personal assistant that helps increase workflow efficiency.
We used Flutter to create the frontend for the web app which provides versatility to turn it into a mobile records system. We also used the Python libraries Tensorflow and Keras to create our personal assistant.
We ran into issues with asynchronous data display and storing our artificial intelligence model in the cloud.
- We created a clean UI for adding and modifying patients data.
- We implementing a calendar for appointments and patient scheduling into the dashboard of the web app.
- We created AI conversations through a neural network and could display that in a clean format.
- We also created authentication and authorization, and worked heavily on the data storage of the patient data in Firebase Firestore
- We focused on learning how to create a cleaner user interface through Flutter.
- We figured out how to host different objects in a google cloud storage container.
- We learned how to implement a more intelligent neural network
Google for Doctors has an exciting room for improvement by implementing useful assistant capabilities such as searching for different items in the patient database, and searching for helpful information about nearby hospitals and current medications. Additionally, we are excited to see the user interface expand its capabilities and create room for additional data management.