Ocufy, is an Augmented Reality application that enables healthcare providers to quickly and seamlessly access patient notes, diagnoses, and information in real-time using facial recognition and tracking. By instantaneously recalling and logging patient data, Ocufy reduces the time that healthcare providers spend using electronic health records, which helps lower physicians’ and nurse practitioners’ burnout rates, stress levels, and dissatisfaction. This efficiency also provides patients with extra time to consult their attending physician(s), increasing accessibility and potentially decreasing the cost of medical care.

A Sound Mood is a Discord application that uses the Spotify API to track songs and gives feedback based on the songs that users listen to. If users play songs that could harm their mood (sad songs), or songs that could decrease productivity and cause the user to be distracted (songs with aggressive themes), then the bot will alert the user.
A Sound Mood will seamlessly integrate with your Spotify activities after you have linked Discord and Spotify together in your Discord connections. After doing so, A Sound Mood will keep track of the songs that you’re playing to alert you whenever the current song will harm your wellness based on its genre. Conversely, if you are on a streak of songs that could benefit your wellness, A Sound Mood will reward you by gamifying your wellness and updating you on your “Soundness Streak” and “Wellness Score.” Ultimately, these features will encourage users to keep listening to positive music for extended periods to improve their mental health.

About 1 in 8 U.S. women (about 12%) will develop invasive breast cancer over the course of her lifetime. To ensure that everyone receives their deserved treatment, early detection is vital. Using machine learning, we have developed a program that detects whether a tumor is malignant or benign (given their symptoms or characteristics). To train our model, we used publicly available datasets for breast cancer patients. Using the machine learning algorithm, we implemented a web application where users can input 9 specific characteristics regarding the tumor. The algorithm then returns a breast cancer prediction and confidence value given the corresponding characteristics. We also utilized a MongoDB database for doctors to look up and store their patients 'information securely allowing them to make informed decisions about their healthcare. Because new user inputs and results are continuously added to this database, the pool of resources and references provided for both doctors and patients alike will grow as more individuals use this application.We hope our use of technology will enhance doctor-patient relationships and be utilized as another tool to better detect breast cancer in the future.

SafeSpace is a multi-functional application that serves as a virtual companion for the user. It was coded in Android Studio and is compatible with Android Phones, but there are plans to expand to other operating systems. The app is designed to ease the anxiety/loneliness any user faces through its numerous features, including a mental health check-up, several games, a story-telling option, and a well-developed diary system. Beyond the current prototype, we hope to add other functions, including communication between users, board/card games, oral narration user experience, and daily motivational quotes.

Double-Beat

Skin Detect

Infodemic