AI Diagnostic Platform
AI-Powered Diagnostic Assistance Platform
A diagnostic assistance platform built for healthcare providers that leverages deep learning models to analyze medical imaging (X-rays, CT scans, MRIs) and flag potential anomalies for radiologist review. The platform integrates directly with existing PACS/RIS systems through DICOM and HL7 FHIR standards, providing real-time AI-assisted analysis without disrupting clinical workflows. It is designed to augment — not replace — radiologist expertise by prioritizing critical cases and reducing the backlog of routine scans.
The Challenge
What We Faced
A network of diagnostic centers was facing a critical bottleneck: radiologists were processing 200+ scans daily with an average turnaround of 48 hours for routine cases. Burnout was high, and missed findings on routine scans were becoming a liability. They needed a system that could triage cases intelligently, flag urgent findings immediately, and integrate seamlessly with their existing imaging infrastructure (PACS) without requiring a workflow overhaul.
Our Solution
How We Solved It
We built a cloud-based AI analysis pipeline that processes DICOM images through a multi-model ensemble (CNN + Vision Transformer) trained on 500,000+ annotated medical images. The system automatically triages incoming scans into three priority levels: Critical (immediate review), Elevated (24hr review), and Routine (standard queue). For critical findings, the system sends real-time alerts to the on-call radiologist with annotated heatmaps highlighting regions of concern. The entire pipeline runs on HIPAA-compliant AWS infrastructure with end-to-end encryption.
Outcomes
Key Results
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