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PulseAI
Diagnostic assistant trained on 1.2M imaging studies across 8 departments.
Radiology Backlogs Growing Faster Than Staff
PulseAI's radiology partners faced growing imaging backlogs while diagnostic accuracy depended on scarce specialist availability across 8 departments.
- ↗Average report turnaround exceeded 72 hours
- ↗Inter-reader variability affected diagnostic consistency
- ↗No standardized workflow for AI-assisted review
- ↗FDA and clinical validation requirements for deployment
PulseAI Diagnostic Assistant Platform
We trained and deployed a diagnostic assistant on 1.2M anonymized imaging studies, integrated directly into radiologist workflows with human-in-the-loop review gates.
The platform provides confidence-scored findings, heatmap overlays, and structured reports—while maintaining full audit trails for clinical validation and regulatory review.
Imaging Studies Trained
Radiology Departments
Faster Report Turnaround
Diagnostic Concordance
Audit Trail Coverage
Validation Pathway Ready
What We Built
- ↗Computer vision models trained on multi-modality imaging data
- ↗Radiologist workflow integration with PACS and RIS systems
- ↗Confidence-scored findings with heatmap visualization
- ↗Human-in-the-loop review gates for every AI suggestion
- ↗Structured report generation with FHIR export
- ↗Clinical validation dashboard for ongoing model monitoring
Measurable Results, Real Impact
Radiologists gained an AI co-pilot that accelerated reports without compromising clinical judgment.
- ↗ Computer vision models trained on multi-modality imaging data
- ↗ Radiologist workflow integration with PACS and RIS systems
- ↗ Confidence-scored findings with heatmap visualization
- ↗ Human-in-the-loop review gates for every AI suggestion
- ↗ Structured report generation with FHIR export
Built on Modern, Scalable Technology
AI That Radiologists Actually Use
PulseAI is now deployed across 8 radiology departments—accelerating diagnostics while keeping clinicians in control of every decision.
- ↗ Radiologist workflow integration with PACS and RIS systems
- ↗ Confidence-scored findings with heatmap visualization
- ↗ Human-in-the-loop review gates for every AI suggestion
- ↗ Clinical validation dashboard for ongoing model monitoring
“This isn't AI replacing radiologists—it's AI giving us back time to focus on the cases that need human expertise most.”
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