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A collaborative project to improve healthcare accessibility for Sinhala-speaking users with personalized therapy recommendations, predictive health diagnosis, and healthy food suggestions.

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24-25J-254 - CeylonCare🚀

Sri Lanka faces a significant limitation of non-communicable diseases, including diabetes, cholesterol, and high blood pressure. The project aims to develop a mobile application that integrates traditional Sri Lankan food remedies with modern technology, offering personalized health advice, disease management, and overall well-being to Sri Lankan users.🌟


📚 Components Overview

Component 01: Machine Learning-Based Disorder Prediction

Author: IT21269370 - Pothuwila P. Y. R

In the modern world, disorders such as diabetes and cholesterol are increasingly common due to unbalanced and unhealthy lifestyles. Early detection and accurate diagnostic methods are crucial for effective management and recovery. This research introduces a machine learning-based approach to predict the diagnosis status and severity of these disorders based on user-input symptoms. By analyzing patient records, multiple machine learning models—including ensemble techniques—identify patterns and correlations between symptoms and these conditions.

Key Features:

  • Evaluation of predictive algorithms (decision trees, SVMs, neural networks).
  • Development of an ensemble model for enhanced accuracy.
  • Implementation as a mobile application for user-friendly interaction.

Component 02: Sri Lankan Recommendation System for Healthy Foods

Author: IT21289002 - Sakunika K. K

This system blends traditional Sri Lankan food culture with advanced technology to provide personalized dietary recommendations. It uses comprehensive health data and clinical research to suggest traditional Sri Lankan meals tailored to individual health profiles. 🌾🍲

Key Features:

  • Collection of health and dietary data for personalized user profiling.
  • Advanced machine learning algorithms for meal recommendations.
  • Feedback-based learning for continuously relevant suggestions.
  • Image processing to analyze user adherence to dietary plans.
  • Manual input options for flexible menu planning.

Highlights:

  • Promotes Sri Lanka’s culinary traditions while addressing modern health challenges.
  • Encourages healthier eating habits and improved health outcomes.

Component 03: AR-Based Stress Management for Chronic Conditions

Author: IT21223976 - Yeshmantha W. N

This study focuses on using Augmented Reality (AR) to provide personalized stress management solutions for individuals managing diabetes and hypertension. The AR-based solution combines user feedback and health metrics to create immersive meditation and breathing exercises, guided by a digital avatar. 🌈🧘‍♂️

Key Features:

  • Personalized stress management plans.
  • Bilingual support (Sinhala and English) for accessibility.
  • Visual and verbal guidance through an interactive AR interface.
  • Enhanced user engagement for better outcomes.

Impact:

  • Addresses localized mental health challenges.
  • Promotes well-being through immersive stress relief techniques.

Component 04: AI Chatbot for Sinhala-Speaking Users

Author: IT21227004 - Fernando W. A. T. A

This component introduces an AI chatbot designed to improve healthcare accessibility for Sinhala-speaking users, focusing on managing diabetes and high blood pressure. By integrating Sinhala voice recognition and natural language processing (NLP), the chatbot provides tailored healthcare advice in the user’s native language. 🩺🤖

Key Features:

  • Collection of comprehensive health information (medical history, symptoms, preferences).
  • Personalized healthcare recommendations based on individual profiles.
  • Integration with Sinhala voice recognition for seamless interaction.
  • Regular updates to maintain accuracy and relevance.

Benefits:

  • Bridges healthcare accessibility gaps for non-English speakers.
  • Pioneers personalized healthcare solutions for underserved populations.

🛠️ Technologies Used

  • Machine Learning: Decision Trees, SVMs, Neural Networks, Ensemble Models.
  • Natural Language Processing (NLP): Advanced conversational capabilities.
  • Augmented Reality (AR): Immersive stress management tools.
  • Voice Recognition: Sinhala voice support for better accessibility.
  • Mobile Development: User-friendly applications for health management.

🎯 Objectives

  1. Early detection and management of diabetes and cholesterol using ML-based predictive models.
  2. Personalized dietary plans promoting Sri Lankan culinary traditions.
  3. Stress management through AR-based interactive solutions.
  4. Accessible healthcare advice for Sinhala-speaking users via AI chatbots.

📈 Expected Outcomes

  • Improved early diagnosis and management of chronic health conditions.
  • Personalized and culturally relevant dietary recommendations.
  • Enhanced stress management outcomes with immersive AR.
  • Bridging language gaps in healthcare through AI-driven chatbots.

Used - Backend - Firebase Cors Express

flask

pandas

joblib

Axios

Frontend - Expo React Native Axios UI Kit

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A collaborative project to improve healthcare accessibility for Sinhala-speaking users with personalized therapy recommendations, predictive health diagnosis, and healthy food suggestions.

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