Visualdx.com no longer supports your web browser (Internet Explorer version 9 or lower). See what browsers we support.
A SAUSHEC dermatology resident encounters a patient with a foot rash and uses VisualDx to build a differential and arrive at the correct diagnosis.
A Stony Brook University medical student uses VisualDx to narrow a rash differential diagnosis for her patient and arrive at an accurate diagnosis.
A Harvard medical student writes about a time he encountered a new diagnosis during rounds. He described the rash to his attending and then confirmed what his attending suspected and educated himself on a new-to-him diagnosis.
A dermatology PA sees a patient with severe pruning. Using VisualDx, she was able to test and treat a condition of which she was not aware.
Understanding and treating skin conditions can be a challenge for the non-dermatologist. Enter the new DermExpert.
The key to accurately diagnosing skin conditions starts with the correct morphology, but if you didn't do your medical residency in dermatology, identifying a macule versus a papule can be difficult.
The introduction of Artificial Intelligence (AI) and Machine Learning (ML) to the healthcare space presents a unique opportunity to promote learning and improve pattern recognition when making a skin diagnosis. This is especially relevant when determining morphology as it is vital to identify the lesion correctly to come to an accurate diagnosis for a skin concern.
A Brown University dermatology resident turns to VisualDx to first find the cause of her patient's psoriasis (which was thought to be AGEP), then expand the differential to arrive at the correct psoriatic diagnosis.