Prediction and Categorization Of COVID-19 Related Dermatological Manifestations Using Machine Learning

Autor: Dr. Shubhangi DC, Dr. M.A Waheed2, Nameera Simran, Nameera Simran, Dr. Basavaraj Gadgay
Rok vydání: 2023
Předmět:
DOI: 10.5281/zenodo.7863327
Popis: COVID-19 is global epidemic instigated because of "severe acute respiratory syndrome corona virus 2" .Fever, cough, tiredness, dyspnea, and hypogeusia/ hyposmia are all common signs. Dermatological indications have become more common in recent months among the extrapulmonary indicators associated with COVID-19. Our group proposed a taxonomy based on the polymorphic character of COVID-19-related cutaneous symptoms, which includes the following six primary clinical patterns:Urticarial rash, confluent erythematous / maculopapular / morbilliform rash, papulovesicular exanthem, chilblain-like acral, livedo reticularis / racemosa-like, purpuric "vasculitic" patterns. To offer an evaluation of possible pathophysiological routes of COVID-19- related cutaneous symptoms, this research focuses upon that clinical features & therapeutic treatment of every category. Machine learning algorithms such as SVM, RF, DT, KNN, LR, and NB are used in the analysis.
Databáze: OpenAIRE