The implementation of artificial intelligence (AI) and machine learning (ML) techniques in
healthcare has garnered significant attention in recent years, especially as a result of their …

Despite 30 years as a public health emergency, tuberculosis (TB) remains one of the world's
deadliest diseases. Most deaths are among persons with TB who are not reached with …

In tuberculosis (TB), chest radiography (CXR) patterns are highly variable, mimicking
pneumonia and many other diseases. This study aims to evaluate the efficacy of Google …

This study evaluated how often clinically significant lung nodules were detected
unexpectedly on chest radiographs (CXR) by artificial intelligence (AI)—based detection …

Onychomycosis is a common fungal nail infection that is difficult to diagnose due to its
similarity to other nail conditions. Accurate identification is essential for effective treatment …

Ex vivo lung perfusion (EVLP) enables advanced assessment of human lungs for transplant
suitability. We developed a convolutional neural network (CNN)-based approach to analyze …

Our research evaluates advanced artificial (AI) methodologies to enhance diagnostic
accuracy in pulmonary radiography. Utilizing DenseNet121 and ResNet50, we analyzed …

According to the World Health Organization, Pneumoconiosis affects millions of workers
globally, with an estimated 260,000 deaths annually. The burden of Pneumoconiosis is …

Introduction Deep learning (DL) has significantly advanced medical image classification.
However, it often relies on transfer learning (TL) from models pretrained on large, generic …

Background: While deep learning classifiers have shown remarkable results in detecting
chest X-ray (CXR) pathologies, their adoption in clinical settings is often hampered by the …