The remarkable performance of the Transformer architecture in natural language processing
has recently also triggered broad interest in Computer Vision. Among other merits …

Data drift refers to differences between the data used in training a machine learning (ML)
model and that applied to the model in real-world operation. Medical ML systems can be …

Deep learning has become a popular tool for computer-aided diagnosis using medical
images, sometimes matching or exceeding the performance of clinicians. However, these …

Objective This study aimed to develop an open-source multimodal large language model
(CXR-LLaVA) for interpreting chest X-ray images (CXRs), leveraging recent advances in …

Chest X-ray images are among the most common diagnostic tools for detecting and
managing bronchopneumonia and lung abnormalities, such as those caused by COVID-19 …

This paper addresses the significant problem of identifying the relevant background and
contextual literature related to deep learning (DL) as an evolving technology in order to …

Since the beginning of the COVID-19 pandemic, many different machine learning models
have been developed to detect and verify COVID-19 pneumonia based on chest X-ray …

Background Currently, alternative medical imaging methods for the assessment of
pulmonary involvement in patients infected with COVID-19 are sought that combine a higher …

Purpose To develop an artificial intelligence model that uses supervised contrastive learning
(SCL) to minimize bias in chest radiograph diagnosis. Materials and Methods In this …

In medical imaging, deep learning models can be a critical tool to shorten time-to-diagnosis
and support specialized medical staff in clinical decision making. The successful training of …