This telemedicine platform aims to offer dermatology consultations with state-of-the-art tool and AI-driven diagnostic support.
This tele-dermatology platform aims to offer dermatology consultations with AI-driven diagnostic support. This solution involves the development of a telemedicine platform that integrates advanced machine learning models, cloud infrastructure, data storage, and secure communication channels, all while adhering to HIPAA compliance.
Manual Appointment Scheduling
Limited Access to Dermatological Care
Show Diagnosis Process
Data Security and Compliance Concerns
Inconsistent Data Management
Scalability Challenges
Automated Appointment Scheduling
Virtual Telemedicine Platform
AI-assisted Diagnosis Tool
Implemented HIPAA-Compliant System
Integrated API with EHR
Cloud-native Architecture
AI-Powered Image Classification with CNN
The model is a CNN-based deep learning model, designed to classify images of skin conditions with high accuracy.
Trained on over 50,000 images of different skin conditions using publicly available dermatological datasets.
TensorFlow and Keras were used for model development and training, deployed using AWS SageMaker for scalability.
The CNN model is deployed using AWS Lambda, integrated into the backend for seamless scalability and availability.
Outcomes
Expanded dermatology access, especially in remote areas.
Personalized care and virtual convenience boost satisfaction.
Easily expands services without losing care quality.
Saves time for both patients and dermatologists.
Tech Stack
Sneak Pneak
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