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https://observatorio.fm.usp.br/handle/OPI/51523
Title: | Infrared image method for possible COVID-19 detection through febrile and subfebrile people screening |
Authors: | BRIOSCHI, Marcos Leal; NETO, Carlos Dalmaso; TOLEDO, Marcos de; NEVES, Eduardo Borba; VARGAS, Jose Viriato Coelho; TEIXEIRA, Manoel Jacobsen |
Citation: | JOURNAL OF THERMAL BIOLOGY, v.112, article ID 103444, 12p, 2023 |
Abstract: | This study proposed an infrared image-based method for febrile and subfebrile people screening to comply with the society need for alternative, quick response, and effective methods for COVID-19 contagious people screening. The methodology consisted of: (i) Developing a method based on facial infrared imaging for possible COVID-19 early detection in people with and without fever (subfebrile state); (ii) Using 1206 emergency room (ER) patients to develop an algorithm for general application of the method, and (iii) Testing the method and algorithm effectiveness in 2558 cases (RT-qPCR tested for COVID-19) from 227,261 workers evaluations in five different countries. Artificial intelligence was used through a convolutional neural network (CNN) to develop the algorithm that took facial infrared images as input and classified the tested individuals in three groups: fever (high risk), subfebrile (medium risk), and no fever (low risk). The results showed that suspicious and confirmed COVID-19 (+) cases characterized by temperatures below the 37.5 degrees C fever threshold were identified. Also, average forehead and eye temperatures greater than 37.5 degrees C were not enough to detect fever similarly to the proposed CNN algorithm. Most RT-qPCR confirmed COVID-19 (+) cases found in the 2558 cases sample (17 cases/89.5%) belonged to the CNN selected subfebrile group. The COVID-19 (+) main risk factor was to be in the subfebrile group, in comparison to age, diabetes, high blood pressure, smoking and others. In sum, the proposed method was shown to be a potentially important new tool for COVID-19 (+) people screening for air travel and public places in general. |
Appears in Collections: | Artigos e Materiais de Revistas Científicas - COVID-19 Artigos e Materiais de Revistas Científicas - FM/MNE Artigos e Materiais de Revistas Científicas - LIM/62 Artigos e Materiais de Revistas Científicas - ODS/03 |
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