The Analytic for Hemodynamic Instability (AHI) is a software device that analyzes ECG signals to monitor patients' hemodynamic status, detecting signs of instability defined by low blood pressure combined with high heart rate. It provides clinicians with frequent, updated alerts to increase vigilance for patients at risk of hemodynamic deterioration, serving as an adjunctive monitoring tool alongside other patient data to improve early detection and patient management in clinical settings.
Visage Breast Density is a software application designed to analyze mammography images and classify breast density into categories according to the ACR BI-RADS Atlas 5th Edition. It uses a convolutional neural network to assist radiologists by providing adjunctive information about breast tissue composition, making breast density assessment more efficient.
The Imagio Breast Imaging System is a diagnostic tool that combines optoacoustic imaging and ultrasound to provide detailed structural and functional information about breast abnormalities. It uses AI-based software to help healthcare providers better classify breast masses, thereby improving diagnosis. The device is designed to assist, not replace, mammographic screening or biopsy.
EchoGo Pro is an AI-powered software tool designed to assist physicians in diagnosing coronary artery disease by analyzing stress echocardiography ultrasound images. It processes images acquired during stress echo exams, automatically segments the left ventricle, and uses machine learning to provide a categorical assessment of the likelihood of significant CAD, helping clinicians make more accurate and consistent diagnoses.
WRDensity by Whiterabbit.ai is a software tool that uses deep learning to analyze digital mammography images and automatically assess breast tissue composition according to the ACR BI-RADS 5th Edition breast density categories. It helps radiologists by providing breast density categorization and probability scores, which can improve breast cancer risk assessment and patient management. The software works with various mammography systems and outputs results to PACS and RIS for clinician review.
The CellaVision DC-1 is an automated device that uses artificial intelligence to locate and preclassify white blood cells and characterize red blood cells on peripheral blood smears. It captures microscope images, presents them for operator review, and assists in differential blood cell counting, helping clinical laboratories perform in-vitro hematology analysis more efficiently and accurately.
The VX1 is a cardiac mapping software tool designed to assist clinicians during atrial fibrillation or atrial tachycardia procedures by analyzing 3D anatomical and electrical maps of the heart's atria. Using machine and deep learning algorithms, it identifies complex dispersed electrograms in real-time to help guide electrophysiologists in annotating areas of interest, potentially improving mapping accuracy during catheter ablation procedures.
The EyeBOX is an eye-tracking device designed to assist clinicians in diagnosing concussion by analyzing eye movements. Patients watch a video on a screen while a near-infrared camera records their eye gaze data. The device processes this data using advanced algorithms to detect subtle abnormalities in eye movement that indicate concussion, helping doctors make timely and accurate assessments.
TOMTEC-ARENA is a clinical software package designed for reviewing, quantifying, and reporting medical imaging data primarily related to cardiovascular, fetal, and abdominal structures. It helps clinicians assess structures and functions from various imaging modalities in multiple dimensions, facilitating disease diagnosis through detailed quantifications and advanced visualization tools.
EyeArt is an AI-powered medical software that analyzes retinal images to automatically detect more than mild diabetic retinopathy and vision-threatening diabetic retinopathy in adults with diabetes. It is designed to assist healthcare providers in primary care and eye care settings by providing rapid and reliable detection using color fundus images captured by specified retinal cameras.
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