## 💫 Inspiration

It all started when I found VCR tapes of when I was born! I was simply watching the videos fascinated with how much younger everyone looked when I noticed someone unknown, present in the home videos, helping my mom!
After asking my mom, I found out there used to be a program where Nurses/Caretakers would actually make trips to their homes, teaching them how to take care of the baby, and helping them maneuver the first few months of motherhood!
And so, I became intrigued. Why haven't I heard of this before? Why does it not exist anymore? I researched at the federal, provincial and municipal levels to uncover a myriad of online resources available to first-time mothers/parents which aren't well known, and we decided, let's bring it back, better than ever!

## 👶🏻 What BabyBloom does

BabyBloom, is an all-in-one app that targets the needs of first-time mothers in Canada! It provides a simple interface to browse a variety of governmental resources, filtered based off your residential location, and a partnering service with potential caregivers and nurses to help you navigate your very first childbirth.

## 🔨 How we built it

We’re always learning and trying new things! For this app, we aimed to implement an MVC (Model, View, Controller) application structure, and focus on the user's experience and the potential for this project. We've opted for a mobile application to facilitate ease for mothers to easily access it through their phones and tablets. Design-wise, we chose a calming purple monochromatic scheme, as it is one of the main colours associated with pregnancy!

## 😰 Challenges we ran into

* Narrowing the features we intend to provide!
* Specifying the details and specs that we would feed the algorithm to choose the best caregiver for the patient.
* As the app scaled in the prototype, developing the front-end view was becoming increasingly heavier.

## 😤 Accomplishments that we're proud of

This is the first HackTheNorth for many of us, as well as the first time working with people we are unfamiliar with, so we're rather proud of how well we coordinated tasks, communicated ideas and solidified our final product! We're also pretty happy about all the various workshops and events we attended, and the amazing memories we've created.

## 🧠 What we learned

We learned…

* How to scale our idea for the prototype
* How to use AI to create connections between 2 entities
* Figma tips and Know-how to fast-track development
* An approach to modularize solutions

## 💜 What's next for BabyBloom

We can upgrade our designs to full implementation potentially using Flutter due to its cross-platform advantages, and researching the successful implementations in other countries, with their own physical hubs dedicated to mothers during and after their pregnancy!
## Inspiration

We wanted to create a convenient, modernized journaling application with methods and components that are backed by science. Our spin on the readily available journal logging application is our take on the idea of awareness itself. What does it mean to be aware? What form or shape can mental health awareness come in? These were the key questions that we were curious about exploring, and we wanted to integrate this idea of awareness into our application. The “awareness” approach of the journal functions by providing users with the tools to track and analyze their moods and thoughts, as well as allowing them to engage with the visualizations of the journal entries to foster meaningful reflections.

## What it does

Our product provides a user-friendly platform for logging and recording journal entries and incorporates natural language processing (NLP) to conduct sentiment analysis. Users will be able to see generated insights from their journal entries, such as how their sentiments have changed over time.

## How we built it

Our front-end is powered by the ReactJS library, while our backend is powered by ExpressJS. Our sentiment analyzer was integrated with our NodeJS backend, which is also connected to a MySQL database.

## Challenges we ran into

Creating this app idea under such a short period of time proved to be more challenge than we anticipated. Our product was meant to comprise of more features that helped the journaling aspect of the app as well as the mood tracking aspect of the app. We had planned on showcasing an aggregation of the user's mood over different time periods, for instance, daily, weekly, monthly, etc. And on top of that, we had initially planned on deploying our web app on a remote hosting server but due to the time constraint, we had decided to reduce our proof-of-concept to the most essential cores features for our idea.

## Accomplishments that we're proud of

Designing and building such an amazing web app has been a wonderful experience. To think that we created a web app that could potentially be used by individuals all over the world and could help them keep track of their mental health has been such a proud moment. It really embraces the essence of a hackathon in its entirety. And this accomplishment has been a moment that our team can proud of. The animation video is an added bonus, visual presentations have a way of captivating an audience.

## What we learned

By going through the whole cycle of app development, we learned how one single part does not comprise the whole. What we mean is that designing an app is more than just coding it, the real work starts in showcasing the idea to others. In addition to that, we learned the importance of a clear roadmap for approaching issues (for example, coming up with an idea) and that complicated problems do not require complicated solutions, for instance, our app in simplicity allows for users to engage in a journal activity and to keep track of their moods over time. And most importantly, we learned how the simplest of ideas can be the most useful if they are thought right.

## What's next for Mood for Thought

Making a mobile app could have been better, given that it would align with our goals of making journaling as easy as possible. Users could also retain a degree of functionality offline. This could have also enabled a notification feature that would encourage healthy habits.

More sophisticated machine learning would have the potential to greatly improve the functionality of our app. Right now, simply determining either positive/negative sentiment could be a bit vague.

Adding recommendations on good journaling practices could have been an excellent addition to the project. These recommendations could be based on further sentiment analysis via NLP.
## Inspiration

In 2012 in the U.S infants and newborns made up 73% of hospitals stays and 57.9% of hospital costs. This adds up to $21,654.6 million dollars. As a group of students eager to make a change in the healthcare industry utilizing machine learning software, we thought this was the perfect project for us. Statistical data showed an increase in infant hospital visits in recent years which further solidified our mission to tackle this problem at its core.

## What it does

Our software uses a website with user authentication to collect data about an infant. This data considers factors such as temperature, time of last meal, fluid intake, etc. This data is then pushed onto a MySQL server and is fetched by a remote device using a python script. After loading the data onto a local machine, it is passed into a linear regression machine learning model which outputs the probability of the infant requiring medical attention. Analysis results from the ML model is passed back into the website where it is displayed through graphs and other means of data visualization. This created dashboard is visible to users through their accounts and to their family doctors. Family doctors can analyze the data for themselves and agree or disagree with the model result. This iterative process trains the model over time. This process looks to ease the stress on parents and insure those who seriously need medical attention are the ones receiving it. Alongside optimizing the procedure, the product also decreases hospital costs thereby lowering taxes. We also implemented a secure hash to uniquely and securely identify each user. Using a hyper-secure combination of the user's data, we gave each patient a way to receive the status of their infant's evaluation from our AI and doctor verification.

## Challenges we ran into

At first, we challenged ourselves to create an ethical hacking platform. After discussing and developing the idea, we realized it was already done. We were challenged to think of something new with the same amount of complexity. As first year students with little to no experience, we wanted to tinker with AI and push the bounds of healthcare efficiency. The algorithms didn't work, the server wouldn't connect, and the website wouldn't deploy. We persevered and through the help of mentors and peers we were able to make a fully functional product. As a team, we were able to pick up on ML concepts and data-basing at an accelerated pace. We were challenged as students, upcoming engineers, and as people. Our ability to push through and deliver results were shown over the course of this hackathon.

## Accomplishments that we're proud of

We're proud of our functional database that can be accessed from a remote device. The ML algorithm, python script, and website were all commendable achievements for us. These components on their own are fairly useless, our biggest accomplishment was interfacing all of these with one another and creating an overall user experience that delivers in performance and results. Using sha256 we securely passed each user a unique and near impossible to reverse hash to allow them to check the status of their evaluation.

## What we learned

We learnt about important concepts in neural networks using TensorFlow and the inner workings of the HTML code in a website. We also learnt how to set-up a server and configure it for remote access. We learned a lot about how cyber-security plays a crucial role in the information technology industry. This opportunity allowed us to connect on a more personal level with the users around us, being able to create a more reliable and user friendly interface.

## What's next for InfantXpert

We're looking to develop a mobile application in IOS and Android for this app. We'd like to provide this as a free service so everyone can access the application regardless of their financial status.