dandychux / ahuvista

AhuVista is a high-performance application designed to enhance patient care by predicting medical outcomes using cutting-edge technologies. Built with a stack of Rust, Go, and React

RGR Medical Predictor (Rust, Go, React)

Description: The RGR Medical Predictor is a high-performance application designed to enhance patient care by predicting medical outcomes using cutting-edge technologies. Built with a stack of Rust, Go, and React (RGR), the application leverages the computational efficiency and safety of Rust for data processing and machine learning, the robustness and scalability of Go for backend API development and business logic, and the responsiveness and versatility of React for a dynamic user interface.

Objective: The primary objective of the RGR Medical Predictor is to provide healthcare professionals with a reliable tool for predicting patient outcomes based on clinical data. This predictive capability aims to support clinical decision-making, improve patient management strategies, and enhance the overall efficiency of healthcare services.

Key Features:

Data Processing: Utilizes Rust for its superior performance in handling complex data processing and machine learning tasks, ensuring quick and accurate predictions. API and Business Logic: Developed in Go, the backend supports high concurrency and efficient handling of API requests, facilitating seamless data flow and interaction. User Interface: Implemented with React, the frontend offers an engaging and intuitive user experience, making it easy for medical staff to input data and interpret predictive results. Scalability and Security: Designed to scale seamlessly with increasing data loads while ensuring data security and compliance with healthcare regulations such as HIPAA. Use Cases:

Assisting doctors in assessing patient risks and prognoses. Helping hospitals manage patient care more effectively. Supporting medical research by providing data-driven insights into patient outcomes. This project not only bridges the gap between technology and healthcare but also aims to be a pivotal tool in advancing medical research and patient care.

Tech Stack

Client: React, Zustand, TailwindCSS

Server: Go

Machine Learning: Rust