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dashboard
symptom tracker
medication log
resources
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Project

Atlas Health is a web-based application designed to support individuals experiencing symptoms associated with underdiagnosed conditions such as Polycystic Ovary Syndrome (PCOS), endometriosis, and other related disorders. Many individuals experiencing these conditions face long diagnostic delays and limited access to supportive digital tools.

The application aims to help users track symptoms, manage medications, and better understand potential health patterns so they can communicate more effectively with healthcare providers. By combining symptom tracking, AI-assisted analysis, and educational resources, the platform will empower users to better understand their health while reducing uncertainty during the diagnostic process.

Inspiration

Conditions such as PCOS and endometriosis are frequently underdiagnosed and underrepresented in digital health tools. Many individuals experience symptoms for years before receiving a diagnosis, often due to lack of awareness, difficulty recognizing symptom patterns, or limited access to supportive resources.

Existing health tracking apps rarely focus specifically on these conditions, leaving many individuals without tailored tools to monitor symptoms, manage medications, or learn about potential warning signs. As a result, users may struggle to identify patterns in their symptoms, delay seeking medical attention, and experience emotional stress while navigating the diagnostic process. Project Justification

This project addresses a gap in digital health support for individuals with underdiagnosed conditions. A dedicated web application can provide:

Structured symptom tracking
Medication management tools
Educational resources about potential symptoms and side effects
AI-assisted insights that help users recognize patterns
Emotional and community support

By helping users monitor their health over time, the application can encourage earlier medical consultation and more informed conversations with healthcare professionals.

Key Features

AI Symptom Tracker

This feature allows users to log their symptoms using natural language. Users write a short paragraph describing how they feel, and Gemini AI automatically extracts relevant symptoms from the text. The detected symptoms are stored over time in a symptom diary, allowing users to review their health history.

The system visualizes symptom data through graphs and charts, showing trends such as symptom frequency and intensity over days or weeks. This helps users identify patterns that may otherwise be difficult to notice. Users can also export or screenshot a summarized report to share with their healthcare provider during appointments.

Medication Log

The medication management feature helps users keep track of prescribed treatments. Users can add medications by entering the medication name, dosage, frequency, and scheduled time. Medication information is supported by a medication database to ensure accurate references.

The app displays medications in a daily schedule view, making it easy for users to see what needs to be taken and when. The system also sends reminders through browser, email, or phone notifications to help users take their medication consistently.

Care Coach

The Symptom Explainer Chatbot provides an interactive way for users to learn more about their symptoms. Users can type questions or describe symptoms, and Gemini AI generates responses that explain potential symptom meanings and possible related conditions.

The chatbot also suggests helpful questions users can ask their doctor and can reference previously logged symptom data to provide more personalized responses. This feature helps users better understand their health and prepares them for more informed conversations with healthcare professionals.

Resource Page

The resource page provides trusted information on topics such as diet, infertility, mental health, blood pressure, and cholesterol management to help users better understand and manage PCOS-related symptoms and prepare for informed discussions with their healthcare providers.

Tech Stack

Frontend: React, Vite, Tailwind CSS, JavaScript Backend: FastAPI (Python), Gemini API, Supabase, Google OAuth, OpenFDA API, Node.js

Gemini AI API

We used the Gemini AI API to identify user's primary symptoms and track insights from user-reported information, and we also used it in our care coach chatbot to provide emotional support and guide users to the right resources.