This company provides FDA-cleared AI software for real-time detection of seven critical conditions on abdomen-pelvis CT scans. The a2z-Unified-Triage system simultaneously analyzes images to flag urgent findings, enabling immediate worklist prioritization for radiologists. This solution integrates into existing radiology workflows to enhance the speed and focus of urgent case review.
Funding
Funding not disclosed
Founders
Product
Problem
Radiologists face challenges in accurately and efficiently interpreting complex abdomen-pelvis CT scans, leading to potential oversights in detecting critical conditions. Single-disease AI solutions fail to provide a comprehensive analysis, increasing the risk of missed diagnoses and delayed treatment.
Solution
a2z Radiology AI offers a2z-1, a multi-disease AI model designed to analyze abdomen-pelvis CT scans and identify 21 actionable conditions, ranging from common findings like appendicitis to critical conditions like aortic aneurysms. This AI functions as a comprehensive safety net, providing a second look at radiologist reports to detect subtle patterns and discrepancies that may be missed. By simultaneously evaluating multiple conditions, a2z-1 enhances diagnostic accuracy and contributes to improved patient outcomes. The model has been validated across multiple health systems, demonstrating high performance across all 21 conditions.
Target Audience
The primary target audience includes radiology departments and healthcare systems seeking to improve the accuracy and efficiency of abdomen-pelvis CT scan interpretations.
Features
- Multi-disease detection: Identifies 21 actionable conditions in abdomen-pelvis CT scans.
- AI-driven safety net: Acts as a second reader to ensure no critical findings are missed.
- Comprehensive analysis: Simultaneously evaluates multiple conditions for a holistic assessment.
- Subtle pattern detection: Identifies subtle indicators of disease, such as stranding around the pancreatic body indicative of acute pancreatitis.
- Validated performance: Achieves AUC scores of 0.855-0.970 across all 21 conditions in validation studies.
- Experimental analysis pipeline: Prototype pipeline for analyzing abdomen-pelvis CT scans across 21 findings.