Infrared image method for possible COVID-19 detection through febrile and subfebrile people screening

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Arquivos
art_BRIOSCHI_Infrared_image_method_for_possible_COVID19_detection_through_2023.PDF (3.07 MB)
Citações na Scopus
5
Tipo de produção
article
Data de publicação
2023
DOI
Scopus
Web of Science
Título da Revista
ISSN da Revista
Título do Volume
Editora
PERGAMON-ELSEVIER SCIENCE LTD
Autores
BRIOSCHI, Marcos Leal
TOLEDO, Marcos de
NEVES, Eduardo Borba
VARGAS, Jose Viriato Coelho
Citação
JOURNAL OF THERMAL BIOLOGY, v.112, article ID 103444, 12p, 2023
Projetos de Pesquisa
Unidades Organizacionais
Fascículo
Resumo
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.
Palavras-chave
Infrared imaging, Artificial intelligence, Convolutional neural network
URI
https://observatorio.fm.usp.br/handle/OPI/51523
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Coleções
Artigos e Materiais de Revistas Científicas - FM/MNE
Artigos e Materiais de Revistas Científicas - COVID-19
Artigos e Materiais de Revistas Científicas - LIM/62
Artigos e Materiais de Revistas Científicas - ODS/03