Digi_Sanjeevani
Digi Sanjeevanee is an AI-powered healthcare app with doctor consultation, symptom analysis, hospital locator, medical report insights, and a health chatbot. Built with FastAPI & React + Tailwind CSS.
Created on 5th April 2025
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Digi_Sanjeevani
Digi Sanjeevanee is an AI-powered healthcare app with doctor consultation, symptom analysis, hospital locator, medical report insights, and a health chatbot. Built with FastAPI & React + Tailwind CSS.
The problem Digi_Sanjeevani solves
Access to healthcare is often inefficient, costly, and time-consuming. Patients face several challenges, including:
• Delayed Diagnosis: People struggle to assess their symptoms early, leading to late-stage disease detection.
• Finding the Right Doctor: Booking appointments is often difficult, requiring multiple calls and long waiting times.
• Emergency Situations: Locating the nearest hospital quickly can be a challenge, especially in critical moments.
• Medical Report Complexity: Understanding complex medical reports without professional help is overwhelming.
• Misinformation in Healthcare: Online health advice is often unreliable, making it hard to get accurate medical guidance.
✅ How Digi Sanjeevanee Helps
Digi Sanjeevanee is an AI-powered healthcare assistant designed to make healthcare faster, smarter, and more accessible. It offers:
1️⃣ AI-Powered Symptom Analysis: Users can input symptoms, and AI predicts possible conditions along with severity and next steps.
2️⃣ Doctor Consultation System: A user-friendly appointment booking system lets patients easily connect with the right doctor via video consultations.
3️⃣ Hospital Locator: Quickly finds and maps nearby hospitals using OpenStreetMap API, ensuring fast access to medical facilities.
4️⃣ Medical Report Analysis: Users can upload medical reports (PDF/images), and AI extracts and structures key insights for better understanding.
5️⃣ AI Chatbot for Health Queries: A multilingual chatbot (Hindi/English) answers only health-related questions, providing reliable medical guidance.
🚀 Why It Matters?
Digi Sanjeevanee bridges the gap between patients and healthcare services, making medical assistance faster, safer, and more convenient. Whether it’s analyzing symptoms, finding hospitals, consulting doctors, or decoding reports, our AI-driven platform ensures you get the right help at the right time.
🎯 Empowering users with AI-driven, accessible, and efficient healthcare solution
Challenges we ran into
Building Digi Sanjeevanee came with multiple technical and architectural hurdles. Here’s how we tackled the most important ones:
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🧾 OCR for Medical Report Analysis
We faced issues with extracting clear and structured text from medical report images using pytesseract, especially with low-quality scans and varied layouts. We solved this by applying image preprocessing techniques (like thresholding, grayscale, and resizing) and guiding the AI with prompts to interpret the data meaningfully.
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📦 MongoDB Cursor Handling
When retrieving data using pymongo, cursors and ObjectId types created JSON serialization issues. We fixed this by converting the data into JSON-safe formats and excluding unnecessary fields to streamline API responses.
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🔐 SSL Certificate Errors
While making HTTPS API calls, we encountered SSL certificate verification failures—especially on macOS. The issue stemmed from outdated certificate roots. Updating system certificates and environment variables resolved the problem.
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🌐 CORS Issues in React–FastAPI Integration
During development, API requests from the React frontend to FastAPI backend were blocked by CORS policies. This was solved by enabling CORS middleware for local development and properly configuring origins.
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🗂️ File Upload Problems
Handling uploads for both PDFs and images brought issues like timeouts, unsupported formats, and inconsistent MIME types. We resolved these through proper validation, size restrictions, and better file parsing methods.
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🧠 Inconsistent AI Responses
Sometimes, the AI returned unstructured or inconsistent outputs. We overcame this by improving our prompt structure, validating outputs, and adding fallback responses in case of parsing errors.
🎨 Tailwind Styling Challenges
Maintaining consistent UI design with Tailwind CSS required a well-defined theme, reusable components, and responsive layouts. We standardized color schemes and used utilities effectively for a clean, cohesive UI.
Tracks Applied (1)
HashHacks 7.0
Technologies used
