## Inspiration 🎯

Medication non-persistence is a critical issue affecting patient safety in the United States and beyond. According to studies, "between 40% and 75% of adults fail to take their prescribed medications on time each day" [1], leading to worsening health outcomes, increased hospitalizations, and preventable deaths. Non-adherence can lead to serious complications, including "delirium, hypoglycemia, and acute kidney injury" [2]. Existing digital reminder solutions often suffer from high onboarding friction, making them less accessible to those who need them most—particularly senior citizens and less privileged members of society who may have limited access to or knowledge of modern technology like smartphones or the internet. We were inspired to create MediGuide to address these gaps, providing an inclusive, user-friendly solution that enhances medication adherence and improves patient safety for everyone.

## What It Does 💊

MediGuide is an AI-powered reminder and monitoring system designed to enhance patient safety by ensuring adherence to medication regimens. Here's how it works:
1️⃣ Seamless Onboarding with Healthcare Professionals: Patients are onboarded through a consultation session with a healthcare professional, either in-person or via telehealth. The doctor understands the patient's needs, writes a prescription, and enters it into the MediGuide platform, specifying the patient's preferred method of reminder.
2️⃣ Personalized Reminder Delivery: MediGuide's intelligent AI system identifies the medication and dosage, setting up personalized reminders for the patient via their chosen method—automated phone calls or text messages. Each reminder includes clear, simple instructions tailored to the patient's specific medication regimen.
3️⃣ Monitoring and Feedback: After each reminder, the system prompts the patient to confirm medication intake. It periodically checks in about their experiences, detecting early signs of adverse reactions and prompting timely interventions.
4️⃣ AI-Powered Adaptation: The AI continuously learns from patient behavior, using predictive analytics to adapt and optimize reminders for each individual, improving adherence over time.
By integrating this data-driven approach, MediGuide aims to minimize medication-related risks, reduce hospital readmissions, and ultimately improve overall patient safety.

## How We Built It 🛠️

We built MediGuide using Next.js and Flask for the backend, providing a robust and scalable infrastructure. The frontend was developed with React.js, TypeScript, and shadcn, ensuring a responsive and user-friendly interface. To understand doctors' prescriptions and generate smart, personalized reminders, we utilized top-performing Large Language Models (LLMs). For the phone call reminders, we leveraged advanced conversational voice AI technologies to deliver engaging and accessible interactions with patients who may not be familiar with modern digital devices.

## Challenges We Ran Into 🚧

One of the main challenges we faced was integrating advanced AI technologies within a tight time frame. Developing an AI system that accurately understands and processes doctors' prescriptions required careful tuning of Large Language Models. Ensuring that our platform is accessible to patients with limited technological proficiency was another challenge, as we needed to design interfaces and interaction methods (like phone calls) that are user-friendly for all age groups and technological backgrounds. Additionally, we had to consider compliance with healthcare regulations and patient privacy laws, which added complexity to our development process.

## Accomplishments That We're Proud Of 🎉

We are proud of being able to create MediGuide in under 36 hours for a noble cause. Developing a functional AI-powered system capable of understanding prescriptions, generating personalized reminders, and interacting with patients through conversational voice AI within such a short time frame was a significant achievement. We hope that this creation can eventually evolve into a product that helps more patients take their medications timely and recover faster, improving patient safety for millions across the world.

## What We Learned 📚

Throughout this project, we learned about the complexities surrounding medication adherence and the significant impact it has on patient safety and healthcare costs. We gained valuable experience in integrating advanced AI technologies, such as Large Language Models and conversational voice AI, into a practical application. Additionally, we learned the importance of designing solutions that are accessible and user-friendly for all patients, regardless of their technological proficiency. This project reinforced the value of interdisciplinary collaboration between technology and healthcare to address real-world problems.

## What's Next for MediGuide 🚀

We're excited to hear feedback from our peers and mentors and to speak with actual healthcare practitioners. Our next steps involve engaging with medical professionals to gather insights and validate our solution in real-world settings. We aim to explore avenues of collaboration with hospitals and clinics to integrate MediGuide into existing healthcare systems, ultimately improving patient safety on a larger scale. We're also considering further development to comply with healthcare regulations, enhance AI capabilities, and expand accessibility features to reach more patients.
Citations
## Inspiration

This project was inspired by a team member’s family, his grandparents always have to take medicine but often forget about it. Not only his grandparents forget the medicine also his mom. Although, his mom is very young but in a very fast paced society nowadays people always forget to do small things like taking their pills. Due to this inspiration, we decided to develop a pill reminder, but then we got inspired by a Tik Tok video about a person who has Parkinson’s disease and he couldn’t pick up an individual pill from the container. In end, we decide to create this project that will resolve the problem of people forgetting to take their pills as well as helping people to easily take individual pills.

## What it does

Our project the Delta Dispenser uses an app to communicate with the database to set up a specific time to alert users to take their pills as well as tracking their pills information in the app. The hardware of Delta Dispenser will alert the user when the time is reached and automatically dispense the correct amount of the pills into the container.

## How we built it

The frontend of the app is made with **Flutter**, the app communicates with a **firebase real-time database** to store medicinal and scheduling information for the user. The physical component uses an **embedded microcontroller** called an ESP-32 which we chose for its ability to connect to WiFi and be able to sync with the firebase database to know when to dispense the pills.

## Challenges we ran into

The time constraint was definitely a big challenge and we accounted for that by deciding which features were most important in emphasizing our main idea for this project. These parts include the mechanical indexer of the pills, the interface the user would interact with, and how the database would look for communication with the app and the embedded device.

## Accomplishments that we're proud of

We are most proud of how this project utilized many different aspects of engineering, from mechanical to electrical and software. Our team did a really good job at communicating throughout the design process which made integration at the end much easier.

## What we learned

During this project, we had learned how to flutter to create a mobile app as well as learning how firebase works. Throughout this project, although we only learned a few skills that will be very useful in the future. The most important part was that we were able to develop upon the skills we already had. For example, now we are able to develop hardware that could communicate through firebase.

## What's next for Delta Dispenser

The next steps for the Delta Dispenser include building a fully 3D printed prototype, along with the control box and hopper as shown in the CAD renders. On the software side, we would also like to add the ability for more complicated drug scheduling, while keeping the UI easy enough for anyone to set up. Having another portal that allows a doctor to directly input the information themselves is also a feature we are interested in having.
## Inspiration

We both met virtually a few months ago and bonded over the fact that we had a shopping list of things we wanted to teach ourselves, but were having trouble staying motivated and organizing resources to identify where to start. We came up with the idea for this chrome extension (!Ako = "learning" in Maori!) because we wanted a simple tool that could help us with these problems, and bring us and others on the path of meeting learning goals.

## What it does

Shows a list of saved Learning Playlists, allows user to save a tab into a playlist, save all current tabs in the window as a new playlist, create a new playlist with a name input, and open a learning playlist as a new window.

## How we built it

After creating a basic Figma mockup, we designed and set up a Google Cloud SQL database, then separately worked on the frontend and backend. On the backend, we created a Flask app to act as an intermediary between the extension and the database, and on the frontend we used HTML, JS, and CSS to build out the main functionality (as well as some JQuery).

## Challenges we ran into

Neither of us had extensive experiences with databases or frontend before, so we found this weekend to be challenging overall as we learned what we needed to build what we had in our minds. In particular, we were having trouble connecting the Flask app to the SQL server, and debugging JavaScript functions for the frontend.

## Accomplishments that we're proud of

Building the SQL database on Google Cloud, establishing a secure connection between the server and the Flask app, building a functional chrome extension for the first time!

## What we learned

We learned how to design and connect a SQL database! Even though we're still working on functions in the frontend, that was a great learning curve. We were also beginners to backend web dev, so we learned a great deal about effectively planning UI, scaffolding a chrome extension correctly, encrypting the right information, and structuring files in the most efficient way.

## What's next for Ako Chrome Extension

We're planning on building this out into a more interactive and social-based learning chrome extension, implementing OAuth to allow users to have their own logins and profiles, then integrating things like Slack automatic messaging to let people update communities about their learning progress.