Airway disease is a major healthcare issue that causes at least 3 million fatalities every year.
It is also considered one of the foremost causes of death all around the globe by 2030 …

Artificial intelligence (AI) has great potential to improve the field of critical care and enhance
patient outcomes. This paper provides an overview of current and future applications of AI in …

Early evaluation and diagnosis can significantly reduce the life-threatening nature of lung
diseases. Computer-aided diagnostic systems (CADs) can help radiologists make more …

We propose and demonstrate a novel machine learning algorithm that assesses pulmonary
edema severity from chest radiographs. While large publicly available datasets of chest …

We propose and demonstrate a representation learning approach by maximizing the mutual
information between local features of images and text. The goal of this approach is to learn …

With recent advances in electronic data availability, algorithms and computing power, the
potential of artificial intelligence (AI) in the care of the critically ill patients has increased …

Purpose To develop a machine learning approach for classifying disease progression in
chest radiographs using weak labels automatically derived from radiology reports. Materials …

Medical Vision Language Pretraining (VLP) has recently emerged as a promising solution to
the scarcity of labeled data in the medical domain. By leveraging paired/unpaired vision and …

Chest X-ray radiography (CXR) is among the most frequently used medical imaging
modalities. It has a preeminent value in the detection of multiple life-threatening diseases …

Chest diseases are among the most common worldwide health problems; they are
potentially life-threatening disorders which can affect organs such as lungs and heart …