BMC medical informatics and decision making
Oct 30, 2025
OBJECTIVES: To investigate the feasibility of a deep learning model, using a transfer learning approach, for recognizing high-altitude pulmonary edema (HAPE) on chest X-ray images and exploring its capability for assessing severity.
Tuberculosis (TB) remains a major global health burden, particularly in low-resource, high-prevalence regions. Pediatric TB diagnosis poses challenges with non-specific symptoms and less distinct radiological manifestations than adult TB. Many affect...
Chest X-ray (CXR) represents one of the most widely utilized clinical diagnostic tools for thoracic diseases. Nevertheless, computer-aided diagnosis based on chest radiographs still faces considerable challenges in anomaly detection. Certain lesions ...
Developing a novel artificial intelligence (AI) system that can automatically detect pulmonary arterial hypertension (PAH) after correcting the ventricular septal defect (VSD) and to help clinicians make reasonable treatment plans. We analyzed data f...
PURPOSE: The objective of this study was to create an artificial intelligence (AI) system capable of automatically detecting the positional relationship between an X-ray detector and the patient during anteroposterior chest radiography.
UNLABELLED: Low bone mass (LBM), which can lead to osteoporosis, is often undetected and increases the risk of bone fractures. This study presents OsPenScreen, a deep learning model that can identify low bone mass early using standard chest X-rays (C...
While deep convolutional neural networks (DCNNs) have achieved remarkable performance in chest X-ray interpretation, their success typically depends on access to large-scale, expertly annotated datasets. However, collecting such data in real-world cl...
The COVID-19 pandemic has been the most catastrophic global health emergency of the [Formula: see text] century, resulting in hundreds of millions of reported cases and five million deaths. Chest X-ray (CXR) images are highly valuable for early detec...
BACKGROUND: Manufacturer-defined AI thresholds for chest x-ray (CXR) often lack customization options. Threshold optimization strategies utilizing users' clinical real-world data along with pathology-enriched validation data may better address subgro...
BACKGROUND: Dyspnea is a common cause of hospitalization, posing diagnostic challenges among older adult patients with multimorbid conditions. Chest computed tomography (CT) scans are increasingly used in patients with dyspnea and offer superior diag...
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