ScribeAI

Inspiration

The inspiration for ScribeAI came from the need to streamline and modernize the healthcare industry. Healthcare professionals often have to deal with handwritten notes and records, which can be time-consuming and error-prone.

What it does

We wanted to create a solution that would make the transition to electronic health records (EHRs) more efficient, secure, and reliable - ultimately improving patient care.

How we built it

ScribeAI was built using a combination of advanced technologies. We utilized Optical Character Recognition (OCR) to convert handwritten notes into digital text. Natural Language Processing (NLP) techniques were employed to extract relevant information from the digitized text and structure it into EHRs. The system was designed to be HIPAA-Compliant, with strong encryption and security measures to protect patient data. Doctors and healthcare professionals were given the ability to edit and manage records within the platform, ensuring a secure and dynamic system.

Challenges we ran into

Building ScribeAI presented several challenges. One major challenge was formatting raw information into an intuitive and simplistic manner. Ensuring HIPAA compliance and data security was another hurdle, as we had to implement rigorous encryption and access controls. Integrating the platform into existing healthcare systems and workflows also required overcoming interoperability issues.

Accomplishments that we're proud of

Successfully enabling Tesseract OCR and OpenAPI GPT-3.5 models to interact with each other, coupled to provide a powerful service that can parse physical documents to turn them electronic.

What we learned

We gained deeper insights into the world of AI and how fields like computer vision and natural language processing are able to interact to provide powerful solutions, especially in the field of healthcare. Through this project, we gained deeper insights on LSTM models and how the Tesseract API is dependent on it to analyze our provided images of physical records to convert them into sequential strings.

What's next for ScribeAI

Develop business model to deploy this application to real doctors and healthcare institutions across the world. Upgrade the AI models to be more accurate when analyzing, parsing, and formatting text. Deploying the backend using AWS Elastic Kubernetes Service to monitor our backend in the cloud and enable it to scale.