However, the number of deaths is higher in the elderly population. In the United States of America (USA), the younger population, between 18 and 29 years old, are part of the group age with more cases of COVID-19, followed by people between 50 and 64 years ( 8). Severe symptomatic patients can develop dyspnea, acute respiratory distress syndrome, septic shock, and metabolic acidosis ( 1). A mildly symptomatic condition usually presents fever, dry cough, fatigue, muscle pain, and taste and smell changes, with few patients showing neurological and digestive symptoms ( 7). The incubation period goes from 2 to 14 days. The clinical aspects of COVID-19 are highly variable between individuals, varying in different levels of involvement from asymptomatic to lethal conditions. One year later (August 2021), with more than 3,886,112,928 COVID-19 vaccines applied, the third wave of COVID-19 is being noticed in Europe due to the quick virus adaptations increasing the transmissibility and viral load, with four variants of concern and more than ten others identified ( 6). In August 2020, at least five SARS-CoV-2 virus clade mutations were reported, which have increased the infectivity and viral loads in the population ( 5). August 2021, the mark of 198,778,175 confirmed cases was achieved, with 4,235,559 deaths related to COVID-19 worldwide ( 4).

On January 30, 2021, 1 year after WHO declared COVID-19 as an international public health emergency, confirmed cases achieved 101,406,059 and 2,191,898 deaths ( 4). In December 2020, 1 year after the outbreak, the WHO reported 66,243,918 confirmed cases and 1,528,984 deaths by COVID-19 ( 4). The causative agent, a beta coronavirus 2b lineage ( 1) named severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), was identified on January 7, 2020, by throat swab samples ( 2, 3). The coronavirus disease-2019 (COVID-19) is a viral respiratory disease with high rates of human-to-human contagious and transmission and was first reported in 27 patients with pneumonia of unknown etiology on December 31st, 2019, in Wuhan, China. The explainable model showed the importance of the middle left and superior right lung zones in classifying COVID-19 pneumonia from other lung patterns. The best classification model was XGBoost, with an accuracy of 0.82 and a sensitivity of 0.82. Hyperparameter optimization of XGBoost and Random Forest ensemble tree models is applied using random search. SHAP recursive feature elimination with cross-validation is used to select features. After segmenting the lung in three zones and laterally, a histogram normalization is applied, and radiomic features are extracted. We use 2,611 COVID-19 chest X-ray images and 2,611 non-COVID-19 chest X-rays.

The goal is to provide grounds for understanding the distinctive COVID-19 radiographic texture features using supervised ensemble machine learning methods based on trees through the interpretable Shapley Additive Explanations (SHAP) approach. Our work aims to investigate radiomic features and classification models to differentiate chest X-ray images of COVID-19-based pneumonia and other types of lung patterns. However, COVID-19 pneumonia does not have a defined set of radiological findings. 3Machine Learning Theory and Applications Lab, School of Technology, Pontifical Catholic University of Rio Grande do Sul, PUCRS, Porto Alegre, Brazilīoth reverse transcription-PCR (RT-PCR) and chest X-rays are used for the diagnosis of the coronavirus disease-2019 (COVID-19).2Graduate Program in Biomedical Gerontology, School of Medicine, Pontifical Catholic University of Rio Grande do Sul, PUCRS, Porto Alegre, Brazil.1Medical Image Computing Laboratory, School of Technology, Pontifical Catholic University of Rio Grande do Sul, PUCRS, Porto Alegre, Brazil.

Barros 3 and Ana Maria Marques da Silva 1,2 * Luís Vinícius de Moura 1, Christian Mattjie 1,2, Caroline Machado Dartora 1,2, Rodrigo C.

Pneumonia cxr findings