Scientific Research Publishing

UWB NLOS Signal Recognition Based on Deep Learning ()

However, in indoor environments, non-line-of-sight (NLOS) signals significantly degrade the ranging performance of UWB ...

Deep learning model enables accurate and scalable drug-drug interaction prediction

Managing complex medical conditions often requires the simultaneous use of multiple different drugs, referred to as polypharmacy. While necessary, this significantly increases the risk of drug-drug ...
Frontiers

Deciphering Human Disease Immunity by Harnessing Integrative Multi-Omics and Machine Learning

The field of immunology has long recognized immune system dysregulation as a cornerstone of pathogenesis across a range of human diseases, including ...
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 ...
IEEE

Multi-Label Classification of English Social Media Texts based on Deep Learning Algorithm

Abstract: Multi-label classification of English social media texts has become an important task in natural language processing (NLP). Traditional classification methods have shortcomings in dealing ...
Scientific Research Publishing

Comparative Research in Sentiment Analysis Using Machine Learning Technique ()

In today’s digital background, sentiment analysis has become an essential factor of Natural Language Processing (NLP), offering valuable insights from vast online data sources. This paper presents a ...
IEEE

Multi-label Chest X-ray Image Classification via Category Disentangled Causal Learning

Abstract: Chest X-rays (CXR) are widely used to diagnose chest diseases. Since patients often suffer from multiple diseases simultaneously, it is crucial to identify multiple abnormalities in a single ...
Nature

Active Learning for Multi-Label Classification

Active learning for multi-label classification addresses the challenge of labelling data in situations where each instance may belong to several overlapping categories. This paradigm aims to enhance ...