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HEALTHCARE AI & NLP
HIPAA-Compliant AI Diagnostic Assistant for Diagnostic Imaging
Built a custom medical vision AI model and NLP pipeline that assists radiologists by pre-screening chest X-rays and MRI scans with 98.4% diagnostic accuracy.
Radiology Triage Speed
4.5 hrs → 12 mins
-95%
Diagnostic Accuracy
98.4%
+14%
Patient Scans Processed
1.2M+
Active
Client SectorNational Diagnostic Healthcare Network
Duration8 Months
Core StackPyTorch, Python, DICOM Standard
The Challenge
Radiologists faced severe backlogs processing tens of thousands of daily imaging scans, resulting in critical diagnostic delay risks for acute pathology cases.
Our Engineering Approach
01
Fine-tuned a custom Vision-Language Transformer model on anonymized DICOM medical imaging datasets.
02
Engineered an air-gapped, HIPAA-compliant inference API processing high-resolution scans with sub-second inference speed.
03
Integrated real-time priority queuing for acute findings, alerting emergency care teams instantly.
Key Architectural Highlights
HIPAA-compliant AWS GovCloud enclave with strict air-gapping
Custom PyTorch Vision Transformer fine-tuned on DICOM images
Zero-retention inference pipeline ensuring patient data privacy
“The AI assistant engineered by InnoBrain has dramatically accelerated critical triage in our emergency rooms. Radiologists receive flagged anomalies in minutes rather than hours.”
Dr. Elena Rostova
Chief Medical Information Officer
Technologies Deployed
PyTorchPythonDICOM StandardAWS GovCloudFastAPIDockerTriton Server
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