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InVision Precision Cardiac Amyloid is an automated machine learning-based decision support system, indicated as a screening tool for adult patients aged 65 years and over undergoing cardiovascular assessment using echocardiography. When utilized by an interpreting physician, this device provides information alerting the physician for referral to confirmatory investigations. InVision Precision Cardiac Amyloid is indicated in adult populations over 65 years of age. Patient management decisions should not be made solely on the results of the InVision Precision Cardiac Amyloid.

The InVision Precision Cardiac Amyloid (InVision PCA) is a Software as a Medical Device (SaMD) machine-learning screening algorithm to identify high suspicion of cardiac amyloidosis from routinely obtained echocardiogram videos. The device assists clinicians in the diagnosis of cardiac amyloidosis. The InVision PCA algorithm uses a machine learning process to identify the presence of cardiac amyloidosis. The device inputs images and videos from echocardiogram studies, and it outputs a report suggestive or not suggestive of cardiac amyloidosis. The device has no physical form and is installed as a third-party application to an institution's PACS system.

In Vision Precision LVEF is used to process previously acquired trans thoracic cardiac ultrasound images, and manipulate and make measurements on images using an ultrasound device, personal computer, or a compatible DICOM compliant PACS system to provide an automated estimation of LVEF. This measurement can be used to assist the clinician in a cardiac evaluation. In Vision Precision is indicated for use in patients 22 years and older by sonographers and physicians evaluating cardiac ultrasound.

InVision Precision LVEF is a software as a medical device (SaMD), manufactured by InVision Medical Technology Corporation, intended as an aid in diagnostic review and analysis of echocardiographic data, including the evaluation of left ventricular ejection fraction (LVEF) in cardiovascular ultrasound images in DICOM format. The software interfaces with data files uploaded to a PACS by any ultrasound or data collection equipment. It selects a set of echocardiogram videos of the correct view and generates semi-automatic segmentations of the left ventricle using a machine learning algorithm to form the basis for the calculator of the LVEF output. The analysis results are visualized by the clinician's integrated image view application as adjustable annotations. The user has the option to modify the semi-automatic segmentations suggested by the software. The EF calculation is updated in real-time with the user's modification of the segmentation. A cardiologist can adjust the annotations and the downstream measurement of LVEF prior to finalization.