Case Study
MedAI Mobile: Health Companion
AI-powered mobile diagnostic suite that analyzes patient history to predict potential health risks using neural networks.
The Challenge
Understanding the Problem
Analyzing vast amounts of unstructured medical data to provide accurate early warning signs via a mobile interface.
Our Approach
Utilized deep learning models trained on anonymized datasets to detect patterns invisible to the human eye.
Phase 1
Wearable Integration
Phase 2
Telemedicine
Phase 3
FDA Approval
The Solution
Developed a TensorFlow-based neural network trained on anonymized datasets, deployed via a secure React Native mobile interface.
- 94% Accuracy
- <1s Speed
The Outcome
Improved early verification of cardiac issues by 40% in beta testing groups.
Impact: 94% Accuracy
Development Journey
From Concept to Launch
3 months
Model Training
Trained on 100k+ datasets
2 months
App Dev
Built React Native app
Measurable Impact
Key Results
Primary Outcome
94% Accuracy
Direct business value delivered.
94%
Accuracy
Prediction rate
<1s
Speed
Inference time
Technology Stack
Tools & Frameworks
React NativeTensorFlowFastAPIGoogle CloudDocker
"A breakthrough in early diagnosis technology."
Medical Director, City Hospital