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Maintz L, Welchowski T, Herrmann N, et al. Machine Learning-Based Deep Phenotyping of Atopic Dermatitis: Severity-Associated Factors in Adolescent and Adult Patients. JAMA Dermatol. 2021;doi: 10.1001/jamadermatol.2021.3668.
Maintz, L., Welchowski, T., Herrmann, N., Brauer, J., Kläschen, A. S., Fimmers, R., Schmid, M., Bieber, T., Schmid-Grendelmeier, P., Traidl-Hoffmann, C., Akdis, C., Lauener, R., Brüggen, M. C., Rhyner, C., Bersuch, E., Renner, E., Reiger, M., Dreher, A., Hammel, G., Luschkova, D., & Lang, C. (2021). Machine Learning-Based Deep Phenotyping of Atopic Dermatitis: Severity-Associated Factors in Adolescent and Adult Patients. JAMA dermatology, . https://doi.org/10.1001/jamadermatol.2021.3668
Maintz, Laura, et al. "Machine Learning-Based Deep Phenotyping of Atopic Dermatitis: Severity-Associated Factors in Adolescent and Adult Patients." JAMA dermatology vol. (2021). doi: https://doi.org/10.1001/jamadermatol.2021.3668
Maintz L, Welchowski T, Herrmann N, Brauer J, Kläschen AS, Fimmers R, Schmid M, Bieber T, Schmid-Grendelmeier P, Traidl-Hoffmann C, Akdis C, Lauener R, Brüggen MC, Rhyner C, Bersuch E, Renner E, Reiger M, Dreher A, Hammel G, Luschkova D, Lang C. Machine Learning-Based Deep Phenotyping of Atopic Dermatitis: Severity-Associated Factors in Adolescent and Adult Patients. JAMA Dermatol. 2021 Nov 10; doi: 10.1001/jamadermatol.2021.3668. Epub 2021 Nov 10. PMID: 34757407; PMCID: PMC8581798.
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