Advancements in deep learning and computer vision provide promising solutions for
medical image analysis, potentially improving healthcare and patient outcomes. However …

Simple Summary Deep learning has succeeded greatly in medical image-based cancer
diagnosis. To help readers better understand the current research status and ideas, this …

Medical artificial intelligence (AI) offers great potential for recognizing signs of health
conditions in retinal images and expediting the diagnosis of eye diseases and systemic …

Purpose To analyze a recently published chest radiography foundation model for the
presence of biases that could lead to subgroup performance disparities across biologic sex …

Foundation vision-language models are currently transforming computer vision, and are on
the rise in medical imaging fueled by their very promising generalization capabilities …

This survey aims to identify commonly used methods, datasets, future trends, knowledge
gaps, constraints, and limitations in the field to provide an overview of current solutions used …

Abstract Machine learning methods in healthcare have traditionally focused on using data
from a single modality, limiting their ability to effectively replicate the clinical practice of …

Vision-language models such as CLIP are pretrained on large volumes of internet sourced
image and text pairs, and have been shown to sometimes exhibit impressive zero-and low …

Recent advancements in foundation models have shown significant potential in medical
image analysis. However, there is still a gap in models specifically designed for medical …

Uncertainty quantification in automated image analysis is highly desired in many
applications. Typically, machine learning models in classification or segmentation are only …