Deep learning counts river herring across three Massachusetts rivers, matching human estimates

Each spring, river herring populations migrate from Massachusetts coastal waters to begin their annual journey up rivers and ...
Scientific Research Publishing

A Lightweight MobileViT with a Dual-Path Attention Mechanism for MRI Image Classification ()

Deep learning has been successfully applied in the field of medical diagnosis, and improving the accurate classification of ...
Scientific Research Publishing

H-UQ-MFF: Hybrid Uncertainty-Aware Multi-Feature Fusion for Clinically-Translatable Glaucoma Detection with FDA-Compliant Validation ()

Although artificial intelligence (AI) has demonstrated potential in automating glaucoma screening, there is still a significant obstacle in transferring research datasets to actual clinical settings.
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 ...