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ApolloAI is a platform in which doctors and patients can access medical tools in order to promote and benefit local health. While developing ApolloAI, we directed our attention to one critical issue : How come ten million people in poorer countries die from illnesses that could have been easily treated every year? To address this issue, we developed a tool that both doctors and patients in third world countries can use. ApolloAI combines a myriad of powerful libraries and machine learning technologies to accomplish our solution. To start things off, we created two authentication portals for patients and doctors. Here, we use the power of Firebase, an online cloud database that allows us to authenticate users. Doctors and Patients can sign up and log in with divided accounts. Once signed in, they are met with two different experiences. Patients can learn about diseases, seek medical advice, look for potential medications, find clinics near them, and talk with Apollo, our custom medical assistant that can give smart medical advice (using Dialogflow, to build rich and natural conversational experiences). Dialogflow uses a robust neural network to perform Natural Language Processing (NLP). Doctors, however, can access additional features that we have developed just for them. In addition to information about diseases, clinics, and a doctor-oriented Apollo, doctors can also access a convolutional neural network, a machine learning model that can accept, recognize, and then proceed to diagnose infection from a single X-RAY image! Many doctors across the world do not have access to the tools they need to help their patients. We created the Apollo Tool to allow doctors with substandard equipment to help those in need.
- Get dependencies from the
pubspec.yaml - Open
main.dart - Run
open -a Simulator - Run
flutter run
Developers:
- Aryan Vichare
- Soham Manoli