Following unprecedented success on the natural language tasks, Transformers have been
successfully applied to several computer vision problems, achieving state-of-the-art results …

Transformer, one of the latest technological advances of deep learning, has gained
prevalence in natural language processing or computer vision. Since medical imaging bear …

Training segmentation models for medical images continues to be challenging due to the
limited availability of data annotations. Segment Anything Model (SAM) is a foundation …

Traditional biomedical artificial intelligence (AI) models, designed for specific tasks or
modalities, often exhibit limited flexibility in real-world deployment and struggle to utilize …

Background Medicine is inherently multimodal, requiring the simultaneous interpretation
and integration of insights between many data modalities spanning text, imaging, genomics …

Abstract The Segment Anything Model (SAM) is the first foundation model for general image
segmentation. It has achieved impressive results on various natural image segmentation …

Recent advances in deep learning have led to a promising performance in many medical
image analysis tasks. As the most commonly performed radiological exam, chest …

Advancements in deep learning techniques carry the potential to make significant
contributions to healthcare, particularly in fields that utilize medical imaging for diagnosis …

Under the global pandemic of COVID-19, the use of artificial intelligence to analyze chest X-
ray (CXR) image for COVID-19 diagnosis and patient triage is becoming important …

Tuberculosis (TB) is a chronic lung disease that occurs due to bacterial infection and is one
of the top 10 leading causes of death. Accurate and early detection of TB is very important …