Caire Health offers an AI-driven software solution that enhances the speed and accuracy of intracranial hemorrhage (ICH) diagnosis by automatically detecting and classifying emergent pathologies in CT scans. This technology reduces treatment delays and improves patient outcomes by enabling rapid discharge of non-emergent cases, thereby optimizing emergency room operations.
Funding
$125K raised to dateRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.
Founders
Product
Problem
Emergency rooms face challenges in the timely and accurate diagnosis of intracranial hemorrhage (ICH) due to increasing imaging requests and specialist shortages. Delays in diagnosis can lead to poor patient outcomes and increased mortality rates, while slow processing of non-emergent cases contributes to emergency room congestion and resource inefficiencies.
Solution
Caire Health offers an AI-powered software solution designed to improve the speed and accuracy of ICH diagnosis using head CT scans. The software automatically detects and classifies emergent pathologies, enabling rapid identification or rule-out of ICH and its subclassifications, including epidural hematoma (EDH), subdural hematoma (SDH), subarachnoid hemorrhage (SAH), intraventricular hemorrhage (IVH), and intraparenchymal hemorrhage (IPH). It also performs ICH segmentation, midline shift analysis, calvarial fracture detection, and ventricle segmentation, providing comprehensive imaging intelligence to physicians. By expediting the diagnosis of critical cases and facilitating the rapid discharge of patients without emergent findings, Caire Health optimizes emergency room operations and improves patient outcomes.
Target Audience
The primary target audience includes hospitals, emergency rooms, radiologists, and emergency physicians seeking to improve the speed and accuracy of ICH diagnosis and streamline emergency room operations.
Features
- AI-driven detection and classification of ICH and its subtypes
- Automated ICH segmentation and volume quantification
- Midline shift analysis for assessing the severity of brain injury
- Calvarial fracture detection
- Automated ventricle volume quantification
- Native integration with existing EMR and PACS systems
- Compatibility with HIPAA-compliant messaging apps
- Validation studies showing high sensitivity and specificity (>97%) in ICH detection