Hackathon Llama Impatto Roma

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Team of two programmers ready to overturn the Italian health system.

GonzagaBytes

mikimena01

Our innovative healthcare chatbot leverages the power of Llama as a Large Language Model (LLM) and ColPali for embeddings to streamline the retrieval of patient medical records. Designed for seamless integration into healthcare systems, it centralizes information, providing doctors with quick, precise, and reliable access to essential patient data. This eliminates the risk of omissions or misunderstandings in patient care.

For example, consider a scenario where a patient forgets to mention a critical medication they are taking during a consultation. With our chatbot, the doctor can instantly retrieve the patient’s complete medical history, including prescribed medications, ensuring no detail is overlooked. This prevents potential drug interactions or incorrect treatments, significantly improving patient outcomes.

The chatbot’s intuitive interaction mimics human-like communication, delivering information in a language doctors can easily understand, thanks to the advanced capabilities of the LLM. The system is accessible through a Flutter-based app, ensuring cross-platform compatibility and a user-friendly experience.

With a broad market appeal, this solution addresses the critical need for efficient and error-free data management in healthcare, offering scalability and adaptability for various medical contexts. By enhancing communication and reducing administrative burdens, our chatbot empowers healthcare professionals to focus on what matters most—patient care

RAG based chatbot used to retrieve patients' historical records about health, their exams and treatments, delivered with an intuitive Mobile/Desktop Web application accessible only by doctors using Health Cards.

"GonzagaBytes team on Hackathon Llama Impatto Roma Hackathon"

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