AIMC Topic: Semantics

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HCTNet: A hybrid CNN-transformer network for breast ultrasound image segmentation.

Computers in biology and medicine Feb 9, 2023
Automatic breast ultrasound image segmentation helps radiologists to improve the accuracy of breast cancer diagnosis. In recent years, the convolutional neural networks (CNNs) have achieved great success in medical image analysis. However, it exhibit...
Semantics Image Processing, Computer-Assisted Radiologists Learning Neural Networks, Computer Humans
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A prefix and attention map discrimination fusion guided attention for biomedical named entity recognition.

BMC bioinformatics Feb 8, 2023
BACKGROUND: The biomedical literature is growing rapidly, and it is increasingly important to extract meaningful information from the vast amount of literature. Biomedical named entity recognition (BioNER) is one of the key and fundamental tasks in b...
Semantics Data Mining Knowledge Bases
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MedLexSp - a medical lexicon for Spanish medical natural language processing.

Journal of biomedical semantics Feb 2, 2023
BACKGROUND: Medical lexicons enable the natural language processing (NLP) of health texts. Lexicons gather terms and concepts from thesauri and ontologies, and linguistic data for part-of-speech (PoS) tagging, lemmatization or natural language genera...
COVID-19 Language Humans Unified Medical Language System Vocabulary, Controlled Semantics Natural Language Processing
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Ocean oil spill detection from SAR images based on multi-channel deep learning semantic segmentation.

Marine pollution bulletin Feb 1, 2023
One of the major threats to marine ecosystems is pollution, particularly, that associated with the offshore oil and gas industry. Oil spills occur in the world's oceans every day, either as large-scale spews from drilling-rig or tanker accidents, or ...
Ecosystem Deep Learning Water Pollutants, Chemical Semantics Environmental Monitoring Oceans and Seas Radar Petroleum Pollution
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DCSAU-Net: A deeper and more compact split-attention U-Net for medical image segmentation.

Computers in biology and medicine Feb 1, 2023
Deep learning architecture with convolutional neural network achieves outstanding success in the field of computer vision. Where U-Net has made a great breakthrough in biomedical image segmentation and has been widely applied in a wide range of pract...
Neural Networks, Computer Semantics Image Processing, Computer-Assisted
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DeepMPF: deep learning framework for predicting drug-target interactions based on multi-modal representation with meta-path semantic analysis.

Journal of translational medicine Jan 25, 2023
BACKGROUND: Drug-target interaction (DTI) prediction has become a crucial prerequisite in drug design and drug discovery. However, the traditional biological experiment is time-consuming and expensive, as there are abundant complex interactions prese...
COVID-19 Drug Discovery Molecular Docking Simulation Humans Proteins Deep Learning Semantics
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PRA-Net: Part-and-Relation Attention Network for depression recognition from facial expression.

Computers in biology and medicine Jan 24, 2023
Artificial intelligence methods are widely applied to depression recognition and provide an objective solution. Many effective automated methods for detecting depression use facial expressions, which are strong indicators to reflect psychiatric disor...
Semantics Facial Expression Artificial Intelligence Depression Humans
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Error-Correcting Mean-Teacher: Corrections instead of consistency-targets applied to semi-supervised medical image segmentation.

Computers in biology and medicine Jan 24, 2023
Semantic segmentation is an essential task in medical imaging research. Many powerful deep-learning-based approaches can be employed for this problem, but they are dependent on the availability of an expansive labeled dataset. In this work, we augmen...
Semantics Biomedical Research Image Processing, Computer-Assisted Robotics Humans
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SPNet: Structure preserving network for depth completion.

PloS one Jan 24, 2023
Depth completion aims to predict a dense depth map from a sparse one. Benefiting from the powerful ability of convolutional neural networks, recent depth completion methods have achieved remarkable performance. However, it is still a challenging prob...
Semantics Neural Networks, Computer
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Diversity Learning Based on Multi-Latent Space for Medical Image Visual Question Generation.

Sensors (Basel, Switzerland) Jan 17, 2023
Auxiliary clinical diagnosis has been researched to solve unevenly and insufficiently distributed clinical resources. However, auxiliary diagnosis is still dominated by human physicians, and how to make intelligent systems more involved in the diagno...
Natural Language Processing Semantics Language Humans
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