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Predicting the long‐term outcomes of biologics in patients with psoriasis using machine learning
Author(s) -
Emam S.,
Du A.X.,
Surmanowicz P.,
Thomsen S.F.,
Greiner R.,
Gniadecki R.
Publication year - 2020
Publication title -
british journal of dermatology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.304
H-Index - 179
eISSN - 1365-2133
pISSN - 0007-0963
DOI - 10.1111/bjd.18741
Subject(s) - psoriasis , term (time) , medicine , machine learning , artificial intelligence , intensive care medicine , dermatology , computer science , physics , quantum mechanics
Despite the vast amount of data on the efficacy of biologics in psoriasis treatment, therapeutic decision-making is still based on a trial-and-error approach. In a real world setting over 50% of patients needing dose adjustment during therapy and 20-50% of patients experiencing a relapse of the disease requiring a switch to another medication.
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