IEEE

A Hybrid Feature Extraction and Classification Framework for Depression Detection using Deep Learning and Machine Learning Techniques

Abstract: Depression is most common mental disorder that is affecting approximately 280 million individuals in the world. The stigma and lack of acceptance and awareness is still influencing people ...
EurekAlert!

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

BiLSTM, an ICD-11 automatic coding model using MC-BERT and label attention. Experiments on clinical records show 83.86% ...

Deep learning creates virtual multiplexed immunostaining to improve cancer diagnosis

Researchers at the University of California, Los Angeles (UCLA), in collaboration with pathologists from Hadassah Hebrew ...
Frontiers

Modeling, Machine Learning, Bioinformatics and Multi-omics Data in Soil Science

The integration of bioinformatics, machine learning and multi-omics has transformed soil science, providing powerful tools to ...
IEEE

Label Feature Co-Learning for Facial and EEG Emotion Recognition

Abstract: Recognizing human emotions through behavioral and physiological signals is fundamental to overall health. However, since emotion occurs transiently, a semantics mismatch exists between the ...