## Hackers

Scott Blender and Jackie Gan

## Inspiration

This project was inspired by a book called "Hacking Healthcare". It discussed innovations and changes that were needed in the healthcare field and explained how human-centered design can make a positive impact in the field. This project seeks to use human-centered design as the inspiration for how the platform is built.

## What it does

Our application creates an ease-of-use communication pipeline to provide sustainable healthcare alternatives for patients. Our client utilizes Sonr technology to privatize sensitive patient data to allow them to control who has access to their records. In addition, the client helps facilitate communication between patients and doctors to allow doctors to recommend sustainable alternatives besides coming into the office, reducing the effects and need of transportation. These can include telehealth services, non-pharmaceutical interventions, and other sustainable options. By reducing the need for transportation to and from healthcare providers and pharmacies, more effective and sustainable ways can be advanced in the healthcare space for treating patient recovery,

## How we built it

This app is primarily built using golang and utilizes the Motor API built through Sonr. Due to the sensitive content shared across this site, Sonr is a great way to maximize patient privacy and provide confidential communication between patients and doctors.

## Challenges we ran into

Our team were the first users ever to develop a golang app that uses the Sonr platform on a Windows operating environment. This presented many difficulties, and ultimately, led us to having to focus on finishing the design of the backend in Sonr for the web application. This was caused by a persistent error in login authentication. Through this, though, we persisted and continued to develop out our backend system to integrate patient and primary care provider data transfer.

## Accomplishments that we're proud of

We were able to build a semi-working back-end in Sonr! Learning about blockchain, Web3, and what Sonr does inspired me and my teammate to work on developing an app that relies on sensitive data transfer. In addition, we already pitched to the Sonr team at PennApps and received positive feedback on the idea and plan for implementation using Sonr.

## What we learned

We learned a lot about back-end, schemas, objects, and buckets. Schemas, objects, and buckets are the primary ways data is structured in Sonr. By learning the building blocks of how to store, pass, and collect data, we learned how to appropriately construct a data storage solution. In addition, this was our teams first time ever using golang and competing at PennApps, so it was a great experience to learn and new language and make new connections.

## What's next for Sustainabilicare

The future looks bright. With continued support and debugging in using Sonr, we can continue to elevate our project and make it an actual backend solution. We plan on creating a formal pitch, building out a fully functional front-end, and learning more about Sonr structures to enhance the way our backend works.
## Inspiration

Our inspiration for this project was the technological and communication gap between healthcare professionals and patients, restricted access to both one’s own health data and physicians, misdiagnosis due to lack of historical information, as well as rising demand in distance-healthcare due to the lack of physicians in rural areas and increasing patient medical home practices. Time is of the essence in the field of medicine, and we hope to save time, energy, money and empower self-care for both healthcare professionals and patients by automating standard vitals measurement, providing simple data visualization and communication channel.

## What it does

What eVital does is that it gets up-to-date daily data about our vitals from wearable technology and mobile health and sends that data to our family doctors, practitioners or caregivers so that they can monitor our health. eVital also allows for seamless communication and monitoring by allowing doctors to assign tasks and prescriptions and to monitor these through the app.

## How we built it

We built the app on iOS using data from the health kit API which leverages data from apple watch and the health app. The languages and technologies that we used to create this are MongoDB Atlas, React Native, Node.js, Azure, Tensor Flow, and Python (for a bit of Machine Learning).

## Challenges we ran into

The challenges we ran into are the following:

1) We had difficulty narrowing down the scope of our idea due to constraints like data-privacy laws, and the vast possibilities of the healthcare field.

2) Deploying using Azure

3) Having to use Vanilla React Native installation

## Accomplishments that we're proud of

We are very proud of the fact that we were able to bring our vision to life, even though in hindsight the scope of our project is very large. We are really happy with how much work we were able to complete given the scope and the time that we have. We are also proud that our idea is not only cool but it actually solves a real-life problem that we can work on in the long-term.

## What we learned

We learned how to manage time (or how to do it better next time). We learned a lot about the health care industry and what are the missing gaps in terms of pain points and possible technological intervention. We learned how to improve our cross-functional teamwork, since we are a team of 1 Designer, 1 Product Manager, 1 Back-End developer, 1 Front-End developer, and 1 Machine Learning Specialist.

## What's next for eVital

Our next steps are the following:

1) We want to be able to implement real-time updates for both doctors and patients.

2) We want to be able to integrate machine learning into the app for automated medical alerts.

3) Add more data visualization and data analytics.

4) Adding a functional log-in

5) Adding functionality for different user types aside from doctors and patients. (caregivers, parents etc)

6) We want to put push notifications for patients' tasks for better monitoring.
**Inspiration**

Brought up in his rural hometown of Faizabad in India, one of our team members has seen several villagers unable to access modern medical advice. This often led to unfortunate catastrophes that could have been prevented easily. To answer the medical information needs of the lower-income section of society, we created a forum for health-related questions such as medications and diet. We hoped to leverage the decentralized power of blockchain technology to help bridge the gap between quality healthcare advice and the resources of the less fortunate.

**What it does**

Faiza provides a decentralized user experience for posting and answering important medical questions. Each question asked by a user will create a tradeable NFT that is stored on a decentralized database available on the Sonr ecosystem. The prices of these posts are determined by the “karma,” or the number of upvotes that it has. Higher popularity signals increased karma and a larger associated intrinsic value of the “post” NFT. Hence, we create a self-regulating token marketplace to openly trade the created NFTs.

Additionally, we distribute the initial ownership between the post creator and the most upvoted comment to incentivize doctors to provide high-value, relevant information to patients.

Lastly, by using state-of-the-art natural language processing systems, we efficiently perform sentiment analysis on the posts and categorize them by certain tags. Additionally, we filter out relevant comments, deleting ones that are considered spam or derogatory.

**How we built it**

In order to establish a P2P NFT network, we employed Sonr.io, a decentralized network program. Our NFTs are stored on schemas that are pre-defined by us. The Sonr team was very helpful in helping us learn and implement their tech. In particular, we’d like to give a huge shout-out to Ian for helping us understand his speedway API, it really helped speed production :)

To incorporate the NLP, we utilized Cohere to create robust and easily deployable models. We created multiple models such as one to classify the toxicity of comments and another to perform sentiment analysis on a post and categorize it.

Furthermore, we utilized Node for the implementation of the backend and Bootstrap React to build out an aesthetically pleasing front end. Moreover, to facilitate the multiple API calls between our servers, we used Heroku to host them in the cloud and Postman to validate them.

**Challenges we ran into**

To be honest, we weren’t completely familiar with web3 and blockchain. So, it took us a while to conceptually understand Sonr and the integration of its ecosystem. We have to once again thank Ian for the tremendous amount of support he has provided to us on this journey!

Additionally, as we were making API calls between multiple servers (NLP, Node, Web3), they were often conflicting requests. Dealing with the sheer number of requests was difficult to handle and test using Postman.

**Accomplishments that we're proud of**

We’re proud to officially be Web 3.0 Developers :)

Prior to this hackathon, we had little to no experience working with web3 and blockchain technologies. However, this hackathon was a HUGE learning curve. While extremely difficult at first, we are proud to deploy a fully functional decentralized database, with the capability of storing tradeable NFTs and all the elements of a dApp.

**What we learned**

All of us have had a remarkable learning experience. While one of us became proficient in web3, the others learned about testing API calls using Postman, throttling speeds through developer tools, and deploying servers through Heroku CLI.

**What's next for Faiza**

Given the current functionality of Faiza, we hope to include all relevant features in the coming weeks. For instance, we haven’t been able to create a currency that can be liquidated into tangible assets.

Additionally, we hope to implement credibility levels for the users providing medical advice to a post. Using sorting algorithms, we can determine the rank of the importance of comments while displaying them on the user interface.

Lastly, we would love to simplify Faiza and deploy it in the native village of Faizabad, which was the initial fuel for the motivation of the project. We hope to see Faiza making a tangible difference at the grassroots level, changing lives one comment at a time.