**Made by Ella Smith (ella#4637) & Akram Hannoufa (ak\_hannou#7596) -- Team #15**

*Domain: <https://www.birtha.online/>*

## Inspiration

Conversations with friends and family about the difficulty of finding the right birth control pill on the first try.

## What it does

Determines the brand of hormonal contraceptive pill most likely to work for you using data gathered from drugs.com. Data includes: User Reviews, Drug Interactions, and Drug Effectiveness.

## How we built it

The front-end was built using HTML, CSS, JS, and Bootstrap. The data was scraped from drugs.com using Beautiful Soup web-scraper.

## Challenges we ran into

Having no experience in web-dev made this a particularly interesting learning experience. Determining how we would connect the scraped data to the front-end was challenging, as well as building a fully functional multi-page form proved to be difficult.

## Accomplishments that we're proud of

We are proud of the UI design, given it is our first attempt at web development. We are also proud of setting up a logic system that provides variability in the generated results. Additionally, figuring out how to web scrape was very rewarding.

## What we learned

We learned how to use version control software, specifically Git and GitHub. We also learned the basics of Bootstrap and developing a functional front-end using HTML, CSS, and JS.

## What's next for birtha

Giving more detailed and accurate results to the user by further parsing and analyzing the written user reviews. We would also like to add some more data sources to give even more complete results to the user.
## Inspiration

**75% of adults over the age of 50** take prescription medication on a regular basis. Of these people, **over half** do not take their medication as prescribed - either taking them too early (causing toxic effects) or taking them too late (non-therapeutic). This type of medication non-adherence causes adverse drug reactions which is costing the Canadian government over **$8 billion** in hospitalization fees every year. Further, the current process of prescription between physicians and patients is extremely time-consuming and lacks transparency and accountability. There's a huge opportunity for a product to help facilitate the **medication adherence and refill process** between these two parties to not only reduce the effects of non-adherence but also to help save tremendous amounts of tax-paying dollars.

## What it does

**EZPill** is a platform that consists of a **web application** (for physicians) and a **mobile app** (for patients). Doctors first create a prescription in the web app by filling in information including the medication name and indications such as dosage quantity, dosage timing, total quantity, etc. This prescription generates a unique prescription ID and is translated into a QR code that practitioners can print and attach to their physical prescriptions. The patient then has two choices: 1) to either create an account on **EZPill** and scan the QR code (which automatically loads all prescription data to their account and connects with the web app), or 2) choose to not use EZPill (prescription will not be tied to the patient). This choice of data assignment method not only provides a mechanism for easy onboarding to **EZPill**, but makes sure that the privacy of the patients’ data is not compromised by not tying the prescription data to any patient **UNTIL** the patient consents by scanning the QR code and agreeing to the terms and conditions.

Once the patient has signed up, the mobile app acts as a simple **tracking tool** while the medicines are consumed, but also serves as a quick **communication tool** to quickly reach physicians to either request a refill or to schedule the next check-up once all the medication has been consumed.

## How we built it

We split our team into 4 roles: API, Mobile, Web, and UI/UX Design.

* **API**: A Golang Web Server on an Alpine Linux Docker image. The Docker image is built from a laptop and pushed to DockerHub; our **Azure App Service** deployment can then pull it and update the deployment. This process was automated with use of Makefiles and the **Azure** (az) **CLI** (Command Line Interface). The db implementation is a wrapper around MongoDB (**Azure CosmosDB**).
* **Mobile Client**: A client targeted exclusively at patients, written in swift for iOS.
* **Web Client**: A client targeted exclusively at healthcare providers, written in HTML & JavaScript. The Web Client is also hosted on **Azure**.
* **UI/UX Design**: Userflow was first mapped with the entire team's input. The wireframes were then created using Adobe XD in parallel with development, and the icons were vectorized using Gravit Designer to build a custom assets inventory.

## Challenges we ran into

* Using AJAX to build dynamically rendering websites

## Accomplishments that we're proud of

* Built an efficient privacy-conscious QR sign-up flow
* Wrote a custom MongoDB driver in Go to use Azure's CosmosDB
* Recognized the needs of our two customers and tailored the delivery of the platform to their needs

## What we learned

* We learned the concept of "Collections" and "Documents" in the Mongo(NoSQL)DB

## What's next for EZPill

There are a few startups in Toronto (such as MedMe, Livi, etc.) that are trying to solve this same problem through a pure hardware solution using a physical pill dispenser. We hope to **collaborate** with them by providing the software solution in addition to their hardware solution to create a more **complete product**.
## Inspiration

According to the WHO, drug donation today is encountering serious waste in terms of both labor and medical products due to disorganized, massive amount of charity. 80% or donated drugs arrive unsolicited, unexpected, and most notably, unsorted. 62% come with labels in foreign languages that locals cannot decipher. Meanwhile, in other areas, drug cleanup fails to be completed appropriately and cause serious threats to the environment. Dr.Pill was then devised to simplify the medicinal identification process so people, ranging from those simply curious about the pills lying around in the cabinet to those in dire need of quick medical assortment, could utilize the current medical resources for efficiently and sustain-ably.

## What it does

Dr.Phil uses image recognition to instantly identify medicinal pills, from over-the-counter to prescribed counterparts. Functional and consumption information after industry research was carefully selected among many from drugbank database, so contrary to traditional pill identifiers, Dr.Pill could provide much clearer and easier-to-follow insights. It also offers translation for international adoption, especially concerning the influence language barrier can build amidst drug donation.

## How I built it

We created a server using node.js and separately wrote python scripts to use the machine learning APIs (Google OCR, IBM Watson, Translator), then we executed the scripts within the node.js server and rendered the results on frontend templates.

## Challenges I ran into

Fetching data from drugbank and drugs.com was a challenging experience. Certain important drug-related information such as storage methods were inaccessibly as well.

## Accomplishments that I'm proud of

We are proud to have given an attempt towards the life-sciences field for the first time. It was quite different and the topic was very rewarding.

## What I learned

We fortified our experience on using computer vision APIs.

## What's next for Dr.Pill

We hope to add advanced details such as storage details, actual dosages, and voice-interaction functionalities.
Improvement in UX would be another viable integration with better readability of details.