Abstract
Artificial intelligence is a broad branch of computer science that has garnered significant interest in the field of medicine because of its problem solving, decision making and pattern recognition abilities. Machine learning, a subset of artificial intelligence, hones in on the ability of computers to receive data and learn for themselves, manipulating algorithms as they organize the information they are processing. Dermatology is at a particular advantage in the implementation of machine learning due to the availability of large clinical image databases that can be used for machine training and interpretation. While numerous studies have implemented machine learning in the diagnostic aspect of dermatology, less research has been conducted on the use of machine learning in predicting long-term outcomes in skin disease, with only a few studies published to date. Such an approach would assist physicians in selecting the best treatment methods, save patients' time, reduce treatment costs and improve the quality of treatment overall by reducing the amount of trial-and-error in the treatment process. In this review, we aim to provide a brief and relevant introduction to basic artificial intelligence processes, and to consolidate and examine the published literature on the use of machine learning in predicting clinical outcomes in dermatology.
Highlights
Artificial intelligence (AI) is a broad branch of computer science that has garnered significant interest in the field of medicine because of its problem solving, decision making, and pattern recognition abilities
Dermatology is at a particular advantage in the implementation of Machine learning (ML) due to the availability of large clinical image databases that can be used for machine training and interpretation
Studies have already demonstrated the successful use of ML in classification and diagnosis of skin diseases, such as skin cancer [1, 2], eczema [3], psoriasis [4], onychomycosis [5] at a performance level equal or superior to board-certified dermatologists
Summary
Artificial intelligence (AI) is a broad branch of computer science that has garnered significant interest in the field of medicine because of its problem solving, decision making, and pattern recognition abilities. While numerous studies have implemented ML in the diagnostic aspect of dermatology [6], less research has been conducted on the use of ML in predicting long-term outcomes in skin disease, with only a few studies published to date. In an era of personalized medicine, there is a push toward a data-driven approach allowing for accurate prediction of long-term clinical outcomes for individual patients [7,8,9]. Such an approach would assist physicians in selecting the best treatment methods, save patients’ time, reduce treatment costs and improve the quality of treatment overall by reducing the amount of trial-and-error in the treatment process [8]
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