Therapeutic application of machine learning in psoriasis: A Prisma systematic review

Snehal Balvant Lunge; Nandini Sundar Shetty; Vidyadhar R. Sardesai; Priyanka Karagaiah; Paul S. Yamauchi; Jeffrey M. Weinberg; Leon Kircik; Mario Giulini; Mohamad Goldust

doi:10.1111/jocd.15122

Therapeutic application of machine learning in psoriasis: A Prisma systematic review

Snehal Balvant Lunge, Nandini Sundar Shetty, Vidyadhar R. Sardesai, Priyanka Karagaiah, Paul S. Yamauchi, Jeffrey M. Weinberg, Leon Kircik, Mario Giulini, Mohamad Goldust

Research output: Contribution to journal › Review article › peer-review

7 Scopus citations

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.

Original language	English
Pages (from-to)	378-382
Number of pages	5
Journal	Journal of Cosmetic Dermatology
Volume	22
Issue number	2
DOIs	https://doi.org/10.1111/jocd.15122
State	Published - Feb 2023

Keywords

artificial intelligence
dermatology
machine learning
psoriasis

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title = "Therapeutic application of machine learning in psoriasis: A Prisma systematic review",

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.",

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T2 - A Prisma systematic review

AU - Lunge, Snehal Balvant

AU - Shetty, Nandini Sundar

AU - Sardesai, Vidyadhar R.

AU - Karagaiah, Priyanka

AU - Yamauchi, Paul S.

AU - Weinberg, Jeffrey M.

AU - Kircik, Leon

AU - Giulini, Mario

AU - Goldust, Mohamad

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N2 - 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.

AB - 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.

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KW - dermatology

KW - machine learning

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Therapeutic application of machine learning in psoriasis: A Prisma systematic review

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Keywords

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