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.
Basic Morphology
Fifteen percent of all doctor visits involve a skin complaint and up to 48% of the time, patients are misdiagnosed1. If the lesion type is identified correctly, it is much more likely that a clinician will reach the right diagnosis. Here are a few basic lesion types:
Flat


Raised


Fluid-filled



Scale and Crust



Purpura



Loss


In addition to lesion types, there are also 10 basic lesion shapes and configurations: annular, reticular, arcuate, scattered, grouped, serpiginous, linear, targetoid, polycyclic, and whorled. LearnDerm is a free resource to better understand lesion types and basic dermatology.
These are the fundamental lesion types one might see during a skin exam. However, there are hundreds of morphology types and terms that exist. It would be extremely difficult for a nonspecialist to be armed with this information at the point of care based on memorization alone.
Misdiagnosis leads to higher costs and wasted time, and there are not enough dermatologists to handle the case load. This is where ML and AI can come in to help provide important information and improve the recognition of morphology at the point of care.
DermExpert
DermExpert was developed to assist clinicians at the point of care when they are faced with a skin condition. DermExpert allows users to take a picture of a lesion. It then uses machine learning to help narrow down the morphology (trains on 86 types) as well as the patterns that are associated with certain diseases and lesion types. Getting a clinician to a meaningful differential is critical to reaching the correct diagnosis.
The software also aims to train clinicians in the language of the skin exam while providing guidance and helping to build a meaningful differential. By improving pattern recognition and providing extra support, DermExpert can help non-dermatologists become more confident in diagnosing skin conditions.
DermExpert is now available for iOS and Android devices. Learn more and schedule a demo on our website.
References
1. Fleischer AB. Diagnosis of Skin Disease by Nondermatologists. AJMC. https://www.ajmc.com/journals/issue/2000/2000-10-vol6-n10/oct00-504p1149-1156. Published October 1, 2000.