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

被引：10

作者：

Lunge, Snehal Balvant ^{[1
]}

Shetty, Nandini Sundar ^{[1
]}

Sardesai, Vidyadhar R. ^{[1
]}

Karagaiah, Priyanka ^{[2
]}

Yamauchi, Paul S. ^{[3
,4
]}

Weinberg, Jeffrey M. ^{[5
]}

Kircik, Leon ^{[5
]}

Giulini, Mario ^{[6
]}

Goldust, Mohamad ^{[7
]}

机构：

[1] Bharati Vidyapeeth DTU Med Coll & Hosp, Dept Dermatol Venereol & Leprosy, Pune, Maharashtra, India

[2] Bangalore Med Coll & Res Inst, Dept Dermatol, Bangalore, Karnataka, India

[3] Dermatol Inst & Skin Care Ctr, Santa Monica, CA USA

[4] Univ Calif Los Angeles, David Geffen Sch Med, Div Dermatol, Los Angeles, CA USA

[5] Icahn Sch Med Mt Sinai, New York, NY 10029 USA

[6] Johannes Gutenberg Univ Mainz, Univ Med Ctr, Dept Dermatol, Mainz, Germany

[7] Univ Med Ctr Mainz, Dept Dermatol, Mainz, Germany

来源：

JOURNAL OF COSMETIC DERMATOLOGY | 2023年 / 22卷 / 02期

关键词：

artificial intelligence; dermatology; machine learning; psoriasis; SURFACE; VISION; AREA;

D O I：

10.1111/jocd.15122

中图分类号：

R75 [皮肤病学与性病学];

学科分类号：

100206 ;

摘要：

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.

引用

页码：378 / 382

页数：5

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