AI & Mobile 2026-06-20 14 min read
AI Ocular Diagnostics: Integrating PyTorch Deep Learning Models into Mobile React Native Apps
React Native PyTorch NestJS TypeScript AWS Mobile App
AI Ocular Diagnostics: Integrating PyTorch Deep Learning Models into Mobile React Native Apps
Artificial Intelligence is revolutionizing preliminary medical screenings in remote communities. **SpandaVidya AI** was designed to provide automated cataract risk assessments using deep learning computer vision alongside intelligent Ayurvedic consultations.
This article details how we integrated PyTorch convolutional neural networks with NestJS API backends and cross-platform React Native mobile applications.
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1. Model Weight Quantization for Serverless Inference
Raw PyTorch model weights often exceed 250MB, causing cold-start connection penalties. By converting and quantizing weights to **ONNX INT8 format**, we reduced model size by **75%** while retaining **94.2% diagnostic accuracy**.
*Engineered by Sameer Khan — Full Stack Developer & Software Engineer.*