Artificial Intelligence (AI) solutions have been widely used in healthcare, and recent
developments in deep neural networks have contributed to significant advances in medical …

The integration of artificial intelligence (AI) into medical imaging has guided in an era of
transformation in healthcare. This literature review explores the latest innovations and …

Hospital emergency departments frequently receive lots of bone fracture cases, with
pediatric wrist trauma fracture accounting for the majority of them. Before pediatric surgeons …

Learning visual representations of medical images (eg, X-rays) is core to medical image
understanding but its progress has been held back by the scarcity of human annotations …

Building trustworthy and transparent image-based medical artificial intelligence (AI) systems
requires the ability to interrogate data and models at all stages of the development pipeline …

Multimodal medical data fusion has emerged as a transformative approach in smart
healthcare, enabling a comprehensive understanding of patient health and personalized …

Abstract Large Vision-Language Models (LVLMs) have demonstrated remarkable
capabilities in various multimodal tasks. However their potential in the medical domain …

Artificial intelligence (AI) continues to garner substantial interest in medical imaging. The
potential applications are vast and include the entirety of the medical imaging life cycle from …

Abstract Contrastive Language–Image Pre-training (CLIP) has shown remarkable success
in learning with cross-modal supervision from extensive amounts of image–text pairs …

Artificial intelligence and machine learning (AI/ML) models have been adopted in a wide
range of healthcare applications, from medical image computing and analysis to continuous …