Skip to main content
. Author manuscript; available in PMC: 2022 Feb 1.
Published in final edited form as: J Eur Acad Dermatol Venereol. 2020 Nov 22;35(2):546–553. doi: 10.1111/jdv.16979

Table 2.

Accuracy of the AI algorithm, dermatologists, dermatology residents, and general practitioners in overall conditions

n Top-1 Accuracy Top-3 Accuracy
AI algorithm Average dermatologist Average resident Average general practitioner AI algorithm
General 340 41.2% 60.1% 57.8% 49.3% 63.5%
Balanced 340 35.1% 45.2% 42.6% 33.1% 55.1%
Inflammatory 225 38.2% 63.3% 59.1% 50.8% 63.6%
 Dermatitis 82 34.1% 61.4% 52.0% 48.8% 59.8%
 Acne/rosacea 78 47.4% 81.2% 80.8% 73.9% 76.9%
 Autoimmune 34 26.5% 37.3% 36.3% 16.7% 41.2%
 Papulosquamous 17 52.9% 52.9% 47.1% 33.3% 82.4%
Infectious 52 50.0% 59.6% 58.3% 53.2% 69.2%
 Viral 22 50.0% 65.2% 62.1% 51.5% 72.7%
 Fungal 21 52.4% 68.3% 68.3% 71.4% 66.7%
 Bacterial 8 50.0% 20.8% 25.0% 16.7% 62.5%
 Parasitic 1 0% 66.7% 33.3% 0% 0%
Neoplastic 32 37.5% 50.0% 53.1% 41.7% 59.4%
 Benign 28 42.9% 56.0% 59.5% 45.2% 64.3%
 Malignant 4 0.0% 8.3% 8.3% 16.7% 25.0%
Alopecia 15 33.3% 44.4% 44.4% 31.1% 33.3%
 Scarring 8 0% 25.0% 33.3% 16.7% 0%
 Non-scarring 7 71.4% 66.7% 57.1% 47.6% 71.4%
Other 16 68.8% 52.1% 60.4% 47.9% 81.3%

AI, Artificial Intelligence; D, dermatologist; R, residents; GP, general practitioners.