IEEE

EICSeg: Universal Medical Image Segmentation via Explicit In-Context Learning

Abstract: Deep learning models for medical image segmentation often struggle with task-specific characteristics, limiting their generalization to unseen tasks with new anatomies, labels, or modalities ...
InfoQ

Why Most Machine Learning Projects Fail to Reach Production

A monthly overview of things you need to know as an architect or aspiring architect. Unlock the full InfoQ experience by logging in! Stay updated with your favorite authors and topics, engage with ...
New York Post

Chris Cuomo warns CNN’s Scott Jennings over his refusal to stop using the term ‘illegals’: ‘Don’t be a tough guy’

NewsNation host Chris Cuomo warned CNN analyst Scott Jennings on Wednesday that if he keeps using the term “illegal aliens,” somebody might beat him up. Cuomo accused Jennings of acting like a “bully” ...
IEEE

A Multi-Resolution Hybrid CNN-Transformer Network With Scale-Guided Attention for Medical Image Segmentation

Abstract: Medical image segmentation remains a challenging task due to the intricate nature of anatomical structures and the wide range of target sizes. In this paper, we propose a novel U-shaped ...
Medical Xpress

Machine learning can predict patients' responses to antidepressants—while disentangling drug and placebo effects

Depression is one of the most widespread mental health disorders worldwide, affecting approximately 4% of the global population. It is characterized by a persistent low mood, disruptions in typical ...
IEEE

Learning Domain Generalized Remote Sensing Image Segmentation by Multiscale Instance Disentanglement

Abstract: Remote sensing image segmentation is a fundamental task in Earth observation. Rapid development has been made in the past decade owing to the deep learning techniques. Most of the existing ...