![]() ![]() The flare-up of the COVID-19 has increased the need for new effective and faster diagnostic methods than those manual diagnosis provided by the experts. On the other hand, all the models showed a poor precision on viral pneumonia class and confusion in distinguishing it from bacterial pneumonia class, thus a decrease in the overall accuracy. In conclusion, the proposed lightweight model achieved the best overall result in classifying lung diseases allowing it to be used on devices with limited computational power. The results showed that the proposed model with low number of computational layers outperforms the pre-trained benchmark models, achieving an accuracy value of 89.89% while the best pre-trained model (Efficient-Net B2) achieved accuracy of 85.7%. The performance of the proposed model was compared with those obtained by applying transfer learning to the widely used convolutional neural network models. To evaluate the model performance, accuracy, precision, recall, and F1-Score were calculated. The proposed model is designed to classify the X-ray images belonging to one of the four classes that are Healthy, COVID-19, viral pneumonia, and bacterial pneumonia. To address these problems, this study aims to design a lightweight differential diagnosis model based on convolutional neural networks. However, the widely used convolutional neural network architectures typically have many layers causing them to be computationally expensive. Usage of deep learning models is known to be helpful for automated diagnosis of COVID-19 from the X-ray images. The manual examination of these X-ray images may cause problems especially when there is lack of medical staff. Chest x-ray is also used to assess improvement or lack of clinical response in hospitalized patients.X-ray is a useful imaging modality widely utilized for diagnosing COVID-19 virus that infected a high number of people all around the world.Ideally, the chest X-ray should be posteroanterior and lateral, but this will depend on the patient's condition.A chest X-ray also helps to determine pleural effusions or cavitations, as a possible complication.The American Thoracic Society recommends that all patients with a suspicion of nosocomial pneumonia should have a chest x-ray to confirm diagnosis and determine the severity of the disease. ![]() Computed tomography is used in situations when the diagnosis is not clear with a chest x-ray.Chest x-ray findings are usually nonspecific in viral pneumonia.Chest x-rays are also used to evaluate for complications of pneumonia. X-rays can be misleading, because other problems, like lung scarring and congestive heart failure, can mimic pneumonia on x-ray.A normal chest x-ray makes community-acquired pneumonia (CAP) less likely however, CAP is sometimes not seen on x-rays because the disease is either in its initial stages or involves a part of the lung not easily seen by x-ray.X-rays of the chest reveal areas of opacity.Decreased breath sounds and crackles in the physical exam.Patients with the following conditions should be evaluated with a chest X-ray: ![]() Pneumonia is not always seen on x-rays, either because the disease is only in its initial stages, or because it involves a part of the lung not easily seen by x-ray. Chest x-rays can reveal areas of opacity (seen as white) which represent consolidation. OverviewĪn important test for making a diagnosis of pneumonia is a chest x-ray. Associate Editor(s)-in-Chief: Hamid Qazi, MD, BSc, Priyamvada Singh, M.D. ![]() Risk calculators and risk factors for Pneumonia chest x rayĮditor-In-Chief: C. Natural History, Complications and PrognosisĪmerican Roentgen Ray Society Images of Pneumonia chest x rayĪll Images X-rays Echo & Ultrasound CT Images MRIĭirections to Hospitals Treating Pneumonia Differentiating Pneumonia from other Diseases ![]()
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