Disease Pridicta

Introduction

Disease Pridicta is a cutting-edge application designed to predict diseases based on user responses to a series of questions. This application aims to serve both health professionals and patients by providing tailored insights and analytics. By leveraging a questionnaire-based approach, Disease Pridicta offers an engaging and user-friendly experience that aids in early diagnosis and prevention of diseases.

System Overview

Disease Pridicta is a dual-purpose application catering to both health professionals and patients. It provides detailed analytics and insights for doctors while offering easy-to-understand results for patients. The application uses a series of questions to predict potential diseases, making it an invaluable tool for early diagnosis and preventive healthcare.

Functional Requirements

• As a Health Professional, I should be able to access detailed analytics and insights based on patient responses.
• As a Patient, I should be able to answer a series of questions to receive a probable disease prediction.
• As a User, I should be able to view easy-to-understand insights and results from the questionnaire.
• As a User, I should be able to navigate through a user-friendly question flow.

User Personas

• Health Professional: Requires detailed analytics and insights to assist in diagnosis and treatment planning.
• Patient: Seeks easy-to-understand insights and predictions to manage personal health proactively.

Visuals Colors and Theme

• primary: #1A73E8 (a deep blue for trust and professionalism)
• primary_light: #E8F0FE (a light blue for hover states and secondary UI)
• secondary: #FF6F61 (a coral hue for emphasis and links)
• accent: #FFD700 (a vibrant gold for CTAs and active states)
• highlight: #FFA500 (a warm orange for hover states and notifications)
• bg: #F5F5F5 (a light grey for the page background)
• surface: rgba(255, 255, 255, 0.8) (a soft white for card/panel backgrounds)
• text: #333333 (a dark grey for primary text and headings)
• text_muted: #757575 (a medium grey for secondary text and labels)
• border: rgba(200, 200, 200, 0.5) (a subtle grey for borders)

Signature Design Concept

The Disease Pridicta homepage will feature an interactive "Health Journey Map." Users will navigate through a 3D landscape representing different health milestones and checkpoints. Each section of the map will represent a different part of the questionnaire, with animated transitions guiding users from one question to the next. The map will be interactive, allowing users to click on different areas to explore more information or revisit previous questions. This concept will use @react-three/fiber for 3D rendering and gsap for smooth animations and transitions. The experience will be immersive, with subtle sound effects and visual cues enhancing user engagement.

Interaction Model & Motion Direction

The landing page will employ a "parallax" interaction model, creating a layered depth effect as users scroll through the Health Journey Map. Decorative elements will move at varying speeds to create a sense of depth, while the main content will scroll naturally. This approach will provide a visually rich first impression, ideal for engaging both health professionals and patients.

Non-Functional Requirements

• The application must be responsive and accessible on both desktop and mobile devices.
• The system should ensure data privacy and comply with relevant healthcare regulations.
• The application should support multiple languages to cater to a diverse user base.

Tech Stack

• Frontend: React for Web
• Backend: Python, FastAPI
• Database: MySQL or MariaDB, using Alembic for migrations
• AI Models: GPT 5.4 for user-friendly responses
• AI Tools: Litellm for LLM Routing, Langchain
• Local Orchestration: Docker, docker-compose
• Server-side Orchestration: Kubernetes

Assumptions and Constraints

• The application assumes users have basic digital literacy to navigate the questionnaire.
• The system is constrained by healthcare data privacy laws and must ensure secure data handling.
• The application will initially focus on a limited set of diseases, expanding over time based on user feedback and data analysis.

Glossary

• AI Models: Artificial Intelligence models used for processing and generating responses.
• FastAPI: A modern, fast (high-performance) web framework for building APIs with Python.
• LLM Routing: Large Language Model Routing, a method for directing AI model responses.
• Parallax: A scrolling technique that creates an illusion of depth by moving background images slower than foreground images.
• React: A JavaScript library for building user interfaces.
• 3D Rendering: The process of creating three-dimensional images or animations from models.