Authors:	Lunge, Snehal Balvant Shetty, Nandini Sundar Sardesai, Vidyadhar R. Karagaiah, Priyanka Yamauchi, Paul S. Weinberg, Jeffrey Kircik, Leon Giulini, Mario Goldust, Mohamad
Title:	Therapeutic application of machine learning in psoriasis : a Prisma systematic review
Online publication date:	19-Jan-2023
Year of first publication:	2022
Language:	english
Abstract:	Dermatology, being a predominantly visual-based diagnostic field, has found itself to be at the epitome of artificial intelligence (AI)-based advances. Machine learning (ML), a subset of AI, goes a step further by recognizing patterns from data and teaches machines to automatically learn tasks. Although artificial intelligence in dermatology is mostly developed in melanoma and skin cancer diagnosis, advances in AI and ML have gone far ahead and found its application in ulcer assessment, psoriasis, atopic dermatitis, onychomycosis, etc. This article is focused on the application of ML in the therapeutic aspect of psoriasis.
DDC:	610 Medizin 610 Medical sciences
Institution:	Johannes Gutenberg-Universität Mainz
Department:	FB 04 Medizin
Place:	Mainz
ROR:	https://ror.org/023b0x485
DOI:	http://doi.org/10.25358/openscience-8592
Version:	Published version
Publication type:	Zeitschriftenaufsatz
License:	CC BY-NC
Information on rights of use:	https://creativecommons.org/licenses/by-nc/4.0/
Journal:	Journal of cosmetic dermatology Version of Record (VoR)
Publisher:	Wiley-Blackwell
Publisher place:	Oxford
Issue date:	2022
ISSN:	1473-2165
Publisher DOI:	10.1111/jocd.15122
Appears in collections:	DFG-491381577-H