EurekAlert!

A review on multi-view learning

Review re-maps multi-view learning into four supervised scenarios and three granular sub-tiers, delivering the first unified ...
EurekAlert!

Seeing thyroid cancer in a new light: when AI meets label-free imaging in the operating room

Researchers at Duke University combined Dynamic Optical Contrast Imaging (DOCI) with AI to improve thyroid cancer detection ...
InfoQ

Google’s Eight Essential Multi-Agent Design Patterns

Google recently published a guide outlining eight essential design patterns for multi-agent systems, ranging from sequential ...
Scientific Research Publishing

Early Alzheimer’s Disease Detection from Short Speech Samples Using Lightweight, Interpretable Linguistic Markers ()

Based Detection, Linguistic Biomarkers, Machine Learning, Explainable AI, Cognitive Decline Monitoring Share and Cite: de Filippis, R. and Al Foysal, A. (2025) Early Alzheimer’s Disease Detection from ...
Scientific Research Publishing

Boutell, M.R., Luo, J., Shen, X. and Brown, C.M. (2004) Learning Multi-Label Scene Classification. Pattern Recognition, 37, 1757-1771.

ABSTRACT: A binary complete decision table with many-valued decisions is a table with n attributes and 2 n pairwise distinct rows filled with numbers from the set { 0,1 } . Each row of this table is ...
Frontiers

Comparative analysis of machine learning techniques on the BraTS dataset for brain tumor classification

1 Information Statistics Center, Hubei Cancer Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China 2 School of Computer Science and Technology, Hubei Business ...
IEEE

Partial Multi-View Incomplete Multi-Label Learning Network With Quality-Aware Representation Fusion

Abstract: Recently, the topic of multi-view multi-label classification has aroused significant attention from scholars. Plenty of methods adopt an average weighting scheme to merge the features ...
Frontiers

Automatic joint segmentation and classification of breast ultrasound images via multi-task learning with object contextual attention

The segmentation and classification of breast ultrasound (BUS) images are crucial for the early diagnosis of breast cancer and remain a key focus in BUS image processing. Numerous machine learning and ...