Expert Healthcare Assisstance with Online Ease
This project aims to provide assistance in the healthcare centre in two ways. Firstly, providing accessible healthcare services to rural populations by leveraging artificial intelligence and telemedicine technologies. Secondly, by helping the doctor diagnose the test results for major diseases like (brain tumour, breasts cancer, etc) with most accuracy. The web application is designed to function as a virtual medical consultation platform, allowing users to seek medical advice and diagnosis conveniently from nodal centers located in each village, and simultaneously being a platform for doctors to seek assisatnce in generating accurate test result analysis.
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Virtual Consultation: Users can approach the kiosk installed at nodal centers and interact with an AI-powered virtual doctor.
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Input Interface: Patients provide their name, age, and gender through a simple input interface.
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Medical Issue Analysis: Using text-to-speech generation and AI analysis, patients describe their medical issues, which are then analyzed by the AI model.
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Diagnosis Report: The AI generates a detailed diagnosis report, including symptoms, detected problems, suggested treatment, and whether the condition is chronic.
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Telemedicine Integration: For chronic conditions, users can connect with a doctor via video call for personalized consultation and further discussion.
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User-Friendly Interface: The web application features a user-friendly interface tailored for rural populations, ensuring ease of use and accessibility.
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Advanced Diagnosis Algorithms: Utilizes state-of-the-art algorithms to analyze medical reports and provide accurate diagnosis results.
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Multi-Disease Detection: Capable of detecting various diseases including breast cancer, brain tumors, and other common ailments.
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Customizable Reporting: Generates comprehensive reports with detailed insights into the diagnosis, allowing doctors to customize reports according to their preferences.
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Integration with Medical Imaging Technologies: Seamlessly integrates with medical imaging technologies such as MRI, CT scan, and mammography to enhance accuracy in diagnosis.
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Real-Time Analysis: Provides real-time analysis of medical reports, enabling doctors to promptly diagnose and initiate treatment plans.
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AI-Powered Recommendations: Offers AI-powered recommendations for further diagnostic tests or treatment options based on the analysis of medical reports.
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Secure Data Handling: Ensures the confidentiality and security of patient data through robust encryption and data handling protocols.
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User-Friendly Interface: Features an intuitive and user-friendly interface designed to streamline the diagnostic process for healthcare professionals.
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Collaborative Diagnosis: Facilitates collaborative diagnosis by allowing multiple healthcare professionals to review and contribute to the diagnosis process.
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Scalability: Designed to be scalable to handle a large volume of medical reports efficiently, catering to the needs of busy healthcare facilities.
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Continuous Improvement: Committed to continuous improvement through updates and enhancements based on feedback from healthcare professionals and advancements in medical technology.
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Compliance with Regulatory Standards: Adheres to regulatory standards and guidelines for medical software, ensuring compliance with healthcare industry regulations.
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Technical Support and Training: Provides comprehensive technical support and training resources to assist healthcare professionals in using the web app effectively.
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Integration with Electronic Health Records (EHR): Integrates seamlessly with electronic health record systems to streamline the workflow and access patient information securely.
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Feedback Mechanism: Incorporates a feedback mechanism to gather input from healthcare professionals and patients for further improvement of the web app's functionality and accuracy.
- Machine Learning: ML models are utilized for medical issue analysis and diagnosis.
- Text-to-Speech Generation: Text-to-speech technology is employed for converting patient descriptions into text for analysis.
- Telemedicine Platform: Integration with a telemedicine platform enables video calls with doctors for personalized consultations.
- Web Development: The frontend and backend of the web application are developed using modern web development technologies such as HTML, CSS, JavaScript, and Python.
- AI Analysis: Advanced AI algorithms analyze patient descriptions to provide accurate diagnoses.
- Orkes: For designing the entire workflow of the project.
- Vonage Video API: In order to connect the kiosk machine witht the doctors for the telemedicine consultation on a live video call.
- Postman GenAI API: In order to have the perfect Generative AI model ready to assist the rural population after recieveing the speech-to-text promts from the user.
- Neurelo: For the right implemetation on MongoDB
To set up the web application locally or deploy it to a server, follow these steps:
- Clone this repository to your local machine.
- Install the necessary dependencies.
- Run the application server.
- Access the application through a web browser.
- Follow the on-screen instructions to provide input and receive a diagnosis.
This project is developed as an initiative with HackThisFall24.