AI-Powered Telehealth Portal
Neural Net diagnostic scanner integrated with HIPAA-compliant WebRTC stream
The Opportunity
Ensuring strict medical privacy guidelines (HIPAA) while deploying complex machine learning models that identify neural micro-anomalies in real-time during peer-to-peer physician consultations.
The Methodology
Discovery & Planning
Comprehensive analysis of requirements, user needs, and technical constraints.
Development & Execution
We designed isolated, secure API wrappers built in Python to execute convolutional Neural Net operations locally on server nodes, streaming peer-to-peer physician consultations through end-to-end encrypted tunnels.
Testing & Launch
Rigorous quality assurance, performance optimization, and seamless deployment.
The Solution
Convolutional neural networks built on TensorFlow for anomaly tagging.
Convolutional neural networks built on TensorFlow for anomaly tagging.
HIPAA-compliant, end-to-end encrypted WebRTC video streaming.
HIPAA-compliant, end-to-end encrypted WebRTC video streaming.
Isolated API microservices in FastAPI securing scan records.
Isolated API microservices in FastAPI securing scan records.
Dynamic, easy-to-use patient timeline visualizations in Next.js.
Dynamic, easy-to-use patient timeline visualizations in Next.js.
Tech Stack
Modern technologies and frameworks used to build this solution.