IEEE

Hierarchy-Aware and Knowledge-Guided Learning for Multi-Label Classification of Retinal Diseases from Fundus Images

Abstract: Retinal diseases (RD) are major causes of global vision impairment. Automated diagnosis using fundus images has significant clinical value, particularly in multi-label classification of RD.
IEEE

Learning Compact Semantic Information and Reliable Pseudo-labels for Incomplete Multi-View Multi-Label Classification

Abstract: Multi-view data encompasses various data types, including multi-feature, multi-sequence, and multi-modal data. Multi-view multi-label classification aims to leverage the rich semantic ...
The Lancet

Classification accuracy of a hierarchical molecular inference-based deep-learning system for CNS tumour diagnosis: a multi-institutional, retrospective study

aLaboratory of Pathology, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA bCancer Data Science Laboratory, Center for Cancer Research, National ...
EurekAlert!

Label attention meets deep learning: a novel model for ICD-11 automatic classification of Chinese EMRs

Electronic medical records (EMRs) enable healthcare institutions to digitally document patients’ clinical conditions, treatment processes, and diagnostic outcomes, supporting paperless clinical ...
C&EN

Bridging Deep Learning and In Situ Spectroelectrochemistry: A Hybrid Framework for Uncovering Fundamental Insights of Multi-Electron Processes

Energy and Environment Science & Technology, Idaho National Laboratory, Idaho Falls, Idaho 83415, United States ...