GreedAI

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Inspiration

What it does

GreedAI introduces an innovative hospital management system that employs Artificial Intelligence (AI) to prioritize patient appointments effectively. Leveraging machine learning and a greedy sorting algorithm, our system evaluates the urgency of medical cases and organizes patient appointments accordingly. This ensures that critical cases receive prompt attention, while efficiently managing the overall flow of patients, thereby reducing wait times and optimizing healthcare professional schedules.

How we built it

We built GreedAI using a combination of advanced machine learning techniques and efficient sorting algorithms. The core of our system is based on a greedy algorithm that sorts patient cases based on urgency, determined through AI analysis of medical information and symptoms. The system is integrated into a user-friendly platform, backed by MongoDB for robust and scalable data management, ensuring secure and efficient handling of patient records and appointment details.

Challenges we ran into

One of the biggest challenges was ensuring accurate and ethical AI decision-making in prioritizing patient cases. Balancing the urgency of medical conditions with fair and equitable treatment of all patients was crucial. Additionally, integrating the AI system with MongoDB posed technical challenges, requiring us to develop a seamless interface between our algorithm and the database.

Accomplishments that we're proud of

We are proud of creating a system that not only addresses a real-world problem but does so in a manner that is both innovative and practical. Our platform stands out for its ability to reduce patient wait times and streamline hospital workflows, which is a significant step towards improving healthcare services. The positive feedback from initial trials and the potential impact of our solution on the healthcare industry are particularly gratifying.

What we learned

We gained insights into the complexities of medical data handling and the ethical considerations in AI-driven healthcare solutions. The technical skills in AI, database management, and system integration were invaluable learnings as well.

What's next for GreedAI

Looking ahead, we aim to refine GreedAI further, incorporating more advanced AI capabilities and expanding the range of medical conditions it can assess. We plan to pilot our system in more healthcare facilities for broader testing and feedback. Long-term, we envision GreedAI becoming an integral part of healthcare systems worldwide, continually evolving to meet the dynamic demands of patient care and medical management.

Built With

Submitted to

HackED 2024

Created by

My work involved developing an algorithm that combines machine learning method to prioritize patient appointments efficiently. I focused on ensuring the model's ethical and accurate assessment of medical urgency, involving extensive data analysis and preprocessing. Additionally, I managed the training and testing phases, refining the model for optimal performance in real-world healthcare settings. This contribution was crucial in realizing GreedAI's vision of improving healthcare accessibility and efficiency.

Muhammad Hafiz Azhari
I worked to finalize the overall design, focusing heavily on the backend design. I help Hafiz and Yashdeep connect between the frontend and the backend, and we use MongoDB for the project.

Quoc Dinh
My work involved working with the design and coding for the frontend design for the website and the usage of Flask to start a server to enter the data into the database along with Hafiz. I also implemented the greedy sorting algorithm for appointment scheduling to sort take the required data from the databases and classes defined

ysdhimself Dadiala

Updates

Muhammad Hafiz Azhari started this project — Jan 07, 2024 12:14 PM EST

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