Kappa consistency ranges.

<div><p>Gallbladder cancer, a common yet often under diagnosed malignancy, is typically characterized by late detection and a poor prognosis. The rise of deep learning has introduced new methods for its early identification through B-ultrasound imaging, but there are still challenges of...

Full description

Saved in:

Bibliographic Details
Main Author:	Jia Li (160557) (author)
Other Authors:	Yu-Qian Zhou (7449311) (author)
Published:	2025
Subjects:	Biochemistry Biotechnology Space Science Biological Sciences not elsewhere classified Information Systems not elsewhere classified wider clinical use reducing annotation costs outperforming existing methods introduced new methods common yet often branch loss function achieve comparable results 912 &# 8212 using active learning combine active learning tackle related challenges identifying additional features leverages data correlation inefficient data labeling novel classification algorithm enhance feature extraction gallbladder ultrasound dataset supervised learning integration supervised learning feature extraction deep learning still challenges full dataset clustering features ultrasound imaging ultrasound images labeled data typically characterized poor prognosis paper introduces order information mshop module model stability late detection fine textures findings demonstrate effectively captures early identification diagnosed malignancy
Tags:	Add Tag No Tags, Be the first to tag this record!

Kappa consistency ranges.

Similar Items