ArticleDiagnostics (Basel, Switzerland)2021
Artificial Intelligence Applied to Chest X-ray for Differential Diagnosis of COVID-19 Pneumonia.
Article in Diagnostics (Basel, Switzerland), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
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12 citing papers in PubMed, 22 citations in OpenAlex.
- Diagnostic discordance and differential diagnoses of community-acquired pneumonia in the emergency department.BMC emergency medicine · 2026Article
- Revolutionizing non-traumatic acute care: a review of the role of artificial intelligence and machine learning in triaging and diagnosis.Acute and critical care · 2026Article
- Diagnostic Performance of Artificial Intelligence in Detecting COVID-19 Pneumonia on Chest Imaging.Cureus · 2026Review
- Artificial Intelligence Applied to Chest X-ray: A Reliable Tool to Assess the Differential Diagnosis of Lung Pneumonia in the Emergency Department.Diseases (Basel, Switzerland) · 2023Article
- Ten Issues for Updating in Community-Acquired Pneumonia: An Expert Review.Journal of clinical medicine · 2023Review
- A new classification method for diagnosing COVID-19 pneumonia based on joint CNN features of chest X-ray images and parallel pyramid MLP-mixer module.Neural computing & applications · 2023Article
- Inter- and Intra-Observer Agreement When Using a Diagnostic Labeling Scheme for Annotating Findings on Chest X-rays-An Early Step in the Development of a Deep Learning-Based Decision Support System.Diagnostics (Basel, Switzerland) · 2022Article
- Low-cost thermal imaging with machine learning for non-invasive diagnosis and therapeutic monitoring of pneumonia.Infrared physics & technology · 2022Article
- External Validation of Deep Learning Algorithms for Radiologic Diagnosis: A Systematic Review.Radiology. Artificial intelligence · 2022Article
- The role of artificial intelligence in plain chest radiographs interpretation during the Covid-19 pandemic.BJR open · 2022Review
- Application of Table Tennis Ball Trajectory and Rotation-Oriented Prediction Algorithm Using Artificial Intelligence.Frontiers in neurorobotics · 2022Article
- Evaluating Deep Neural Network Architectures with Transfer Learning for Pneumonitis Diagnosis.Computational and mathematical methods in medicine · 2021Article
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Authors and funding
13 authors at 6 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
We assessed the role of artificial intelligence applied to chest X-rays (CXRs) in supporting the diagnosis of COVID-19. We trained and cross-validated a model with an ensemble of 10 convolutional neural networks with CXRs of 98 COVID-19 patients, 88 community-acquired pneumonia (CAP) patients, and 98 subjects without either COVID-19 or CAP, collected in two Italian hospitals. The system was tested on two independent cohorts, namely, 148 patients (COVID-19, CAP, or negative) collected by one of the two hospitals (independent testing I) and 820 COVID-19 patients collected by a multicenter study (independent testing II). On the training and cross-validation dataset, sensitivity, specificity, and area under the curve (AUC) were 0.91, 0.87, and 0.93 for COVID-19 versus negative subjects, 0.85, 0.82, and 0.94 for COVID-19 versus CAP. On the independent testing I, sensitivity, specificity, and AUC were 0.98, 0.88, and 0.98 for COVID-19 versus negative subjects, 0.97, 0.96, and 0.98 for COVID-19 versus CAP. On the independent testing II, the system correctly diagnosed 652 COVID-19 patients versus negative subjects (0.80 sensitivity) and correctly differentiated 674 COVID-19 versus CAP patients (0.82 sensitivity). This system appears promising for the diagnosis and differential diagnosis of COVID-19, showing its potential as a second opinion tool in conditions of the variable prevalence of different types of infectious pneumonia.
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