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Title: Invisible Facial Flushing in COVID-19 Patient Rapidly Detected by Smartphone Application: Subclinical Discovery with a Novel Method
Authors: Arpornsuwan, Manote
Arpornsuwan, Matinun
Keywords: Facial Flushing
Image Enhancement
Image Segmentation
Smartphone Application,
Rock Art Enhancer App
Issue Date: 2020
Abstract: No studies of COVID-19 patients mentioned that facial flushing was a clinical feature that could be found. The invisible facial flushing in COVID-19 patient, unrecognized clinical sign with the naked eye could be detected by the smartphone application and probably was the most common clinical features of Coronavirus disease 2019 as seen in dengue infection and influenza. We discovered the innovative method which can detect invisible facial flushing in dengue infection and influenza by using image enhancement with decorrelation combined image segmentation with K-means clustering. We expect to be able to apply to the COVID-19 patient too, because the clinical signs and symptoms, including the immunopathogenesis of dengue infection and influenza are similar to COVID-19. This is the first case of the COVID-19 patient with the appearance of invisible facial flushing detected by the smartphone application. The innovative application may be useful as a rapid screening tool for diagnosis of COVID-19 patients in the future. This novel screening tool for diagnosis of COVID-19 patients will help all medical service providers the effective screening tool for the recognition and early diagnosis before performing CT scans and real-time RT PCR (rRT-PCR) assays, especially in some health care facilities where could not be performed due to lack of laboratory support. Furthermore, application in active case finding for COVID-19, the key actions to stop transmission is challenging in countries with community transmission.
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