Very impressive! This system can differentiate 26 of the most common skin ailments! Soon your smartphone doctor can do this for you anytime and anywhere!
Credit to Andrew Ng and his deaplearning.ai newsletter![1909.05382] A deep learning system for differential diagnosis of skin diseases: Skin conditions affect an estimated 1.9 billion people worldwide. A shortage
of dermatologists causes long wait times and leads patients to seek
dermatologic care from general practitioners. However, the diagnostic accuracy
of general practitioners has been reported to be only 0.24-0.70 (compared to
0.77-0.96 for dermatologists), resulting in referral errors, delays in care,
and errors in diagnosis and treatment. In this paper, we developed a deep
learning system (DLS) to provide a differential diagnosis of skin conditions
for clinical cases (skin photographs and associated medical histories). The DLS
distinguishes between 26 skin conditions that represent roughly 80% of the
volume of skin conditions seen in primary care. The DLS was developed and
validated using de-identified cases from a teledermatology practice serving 17
clinical sites via a temporal split: the first 14,021 cases for development and
the last 3,756 cases for validation. On the validation set, where a panel of
three board-certified dermatologists defined the reference standard for every
case, the DLS achieved 0.71 and 0.93 top-1 and top-3 accuracies respectively.
For a random subset of the validation set (n=963 c
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