A deep learning-based framework for the malignancy analysis of thyroid lesions in contrast-enhanced ultrasound videos

Artificial Intelligence in Medicine · Published 2026-07-26 · DOI 10.1016/j.artmed.2026.103500

Authors (9)

Aoxiang Yang, Liuyue Li, Ruifan He, Xinlin Zhou, Chengzhi Zheng, Guoping Xu, Jiayu Ren, Xinwu Cui, Xinglong Wu

Abstract

PubPorta does not have an abstract for this article yet.

Read the article at the publisher →

Publication details

Year

2026

Citation

Yang, A., Li, L., He, R., et al. (2026). A deep learning-based framework for the malignancy analysis of thyroid lesions in contrast-enhanced ultrasound videos. Artificial Intelligence in Medicine. https://doi.org/10.1016/j.artmed.2026.103500

Related articles

• Calibration-informed metrics for instance-level predictive reliability in medical AI · Artificial Intelligence in Medicine · 2026 · Same journal
• PDAFormer 3+: A full-scale connected modified transformer with parallel dual attention for 3D medical image segmentation · Artificial Intelligence in Medicine · 2026 · Same journal
• GFASNet: Gait feature attention-driven deep sequential network for dementia-related gait pattern analysis · Artificial Intelligence in Medicine · 2026 · Same journal
• Green artificial intelligence in health applications · Artificial Intelligence in Medicine · 2026 · Same journal
• Deep Cross-Branch Multi-Modal Fusion Network for early Alzheimer’s diagnosis · Artificial Intelligence in Medicine · 2026 · Same journal
• Twin cross contrastive learning with multi-modality fusion for drug–target affinity prediction · Artificial Intelligence in Medicine · 2026 · Same journal
• Application research of dynamic chaotic sequence generation mechanism in pre-hospital emergency data encryption · Artificial Intelligence in Medicine · 2026 · Same journal
• From heatmaps to language: Explainable skin cancer diagnosis using CNN–VLM integration with an expert-annotated dataset · Artificial Intelligence in Medicine · 2026 · Same journal
• Improving organizational processes in healthcare through simulation-driven resource allocation: Methodology and real-world case study · Artificial Intelligence in Medicine · 2026 · Same journal
• Artificial Intelligence and Machine Learning solutions-based oral cancer screening and detection: A scoping review · Artificial Intelligence in Medicine · 2026 · Same journal