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      Machine-Learning-Driven Biomarker Discovery for the Discrimination between Allergic and Irritant Contact Dermatitis

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            Abstract

            Contact dermatitis tremendously impacts the quality of life of suffering patients. Today diagnostic regimes rely on allergy testing, exposure specification, and follow-up visits; however, distinguishing the clinical phenotype of irritant and allergic contact dermatitis remains difficult in some cases. Employing integrative transcriptomic analysis and machine-learning approaches, we aimed to decipher disease-related signature genes to find suitable sets of biomarkers. Random Forest classification identified potential biomarkers to distinguish allergic and irritant contact dermatitis in human skin. Validation experiments and prediction performances on external testing datasets demonstrated potential applicability of the identified biomarker models in the clinic. Capitalizing on this knowledge, novel diagnostic tools can be developed to guide clinical diagnosis of contact allergies.

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            Conference
            REPO4EU
            6 October 2023
            Affiliations
            [1 ] Institute of Biomedicine, University of Eastern Finland, FI-70211 Kuopio, Finland ( https://ror.org/00cyydd11)
            [2 ] Division of Neonatology, Pediatric Intensive Care, and Neuropediatrics, Comprehensive Center for Pediatrics, Department of Pediatrics and Adolescence Medicine, Medical University of Vienna, 1090 Vienna, Austria ( https://ror.org/05n3x4p02)
            [3 ] Institute of Environmental Medicine, Karolinska Institutet, SE-171 77 Stockholm, Sweden ( https://ror.org/056d84691)
            [4 ] Occupational Medicine, Finnish Institute of Occupational Health, 00250 Helsinki, Finland ( https://ror.org/030wyr187)
            [5 ] Institute for Molecular Medicine, University of Helsinki, 00014 Helsinki, Finland ( https://ror.org/040af2s02)
            [6 ] Skin and Allergy Hospital, Helsinki University Central Hospital (HUCH), 00029 HUS Helsinki, Finland ( https://ror.org/02e8hzf44)
            [7 ] Faculty of Medicine and Life Sciences, University of Tampere, 33520 Tampere, Finland ( https://ror.org/033003e23)
            Article
            10.58647/REXPO.23028
            90f8504d-6b91-4724-a56e-b387347256db
            Authors

            Published under Creative Commons Attribution 4.0 International ( CC BY 4.0). Users are allowed to share (copy and redistribute the material in any medium or format) and adapt (remix, transform, and build upon the material for any purpose, even commercially), as long as the authors and the publisher are explicitly identified and properly acknowledged as the original source.

            RExPO23
            2
            Stockholm, Sweden
            25-26 October 2023
            History
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            REPO4EU

            Categories

            Data sharing not applicable to this article as no datasets were generated or analysed during the current study.
            Pharmacology & Pharmaceutical medicine
            Allergic contact dermatitis,artificial intelligence,biomarker,irritant contact dermatitis,machine learning

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