Therapeutic application of machine learning in psoriasis : a Prisma systematic review
| dc.contributor.author | Lunge, Snehal Balvant | |
| dc.contributor.author | Shetty, Nandini Sundar | |
| dc.contributor.author | Sardesai, Vidyadhar R. | |
| dc.contributor.author | Karagaiah, Priyanka | |
| dc.contributor.author | Yamauchi, Paul S. | |
| dc.contributor.author | Weinberg, Jeffrey | |
| dc.contributor.author | Kircik, Leon | |
| dc.contributor.author | Giulini, Mario | |
| dc.contributor.author | Goldust, Mohamad | |
| dc.date.accessioned | 2023-01-19T09:15:37Z | |
| dc.date.available | 2023-01-19T09:15:37Z | |
| dc.date.issued | 2022 | |
| dc.description.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. | en_GB |
| dc.description.sponsorship | Gefördert durch die Deutsche Forschungsgemeinschaft (DFG) - Projektnummer 491381577 | de |
| dc.identifier.doi | http://doi.org/10.25358/openscience-8592 | |
| dc.identifier.uri | https://openscience.ub.uni-mainz.de/handle/20.500.12030/8608 | |
| dc.language.iso | eng | de |
| dc.rights | CC-BY-NC-4.0 | * |
| dc.rights.uri | https://creativecommons.org/licenses/by-nc/4.0/ | * |
| dc.subject.ddc | 610 Medizin | de_DE |
| dc.subject.ddc | 610 Medical sciences | en_GB |
| dc.title | Therapeutic application of machine learning in psoriasis : a Prisma systematic review | en_GB |
| dc.type | Zeitschriftenaufsatz | de |
| jgu.journal.title | Journal of cosmetic dermatology | de |
| jgu.journal.volume | Version of Record (VoR) | de |
| jgu.organisation.department | FB 04 Medizin | de |
| jgu.organisation.name | Johannes Gutenberg-Universität Mainz | |
| jgu.organisation.number | 2700 | |
| jgu.organisation.place | Mainz | |
| jgu.organisation.ror | https://ror.org/023b0x485 | |
| jgu.publisher.doi | 10.1111/jocd.15122 | de |
| jgu.publisher.issn | 1473-2165 | de |
| jgu.publisher.name | Wiley-Blackwell | de |
| jgu.publisher.place | Oxford | de |
| jgu.publisher.year | 2022 | |
| jgu.rights.accessrights | openAccess | |
| jgu.subject.ddccode | 610 | de |
| jgu.subject.dfg | Lebenswissenschaften | de |
| jgu.type.dinitype | Article | en_GB |
| jgu.type.resource | Text | de |
| jgu.type.version | Published version | de |
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