AIMC Topic: Semantics
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Evaluating sentence representations for biomedical text: Methods and experimental results.
Journal of biomedical informatics
Mar 6, 2020
Text representations ar one of the main inputs to various Natural Language Processing (NLP) methods. Given the fast developmental pace of new sentence embedding methods, we argue that there is a need for a unified methodology to assess these differen...
Relation Extraction from Clinical Narratives Using Pre-trained Language Models.
AMIA ... Annual Symposium proceedings. AMIA Symposium
Mar 4, 2020
Natural language processing (NLP) is useful for extracting information from clinical narratives, and both traditional machine learning methods and more-recent deep learning methods have been successful in various clinical NLP tasks. These methods oft...
Using FHIR to Construct a Corpus of Clinical Questions Annotated with Logical Forms and Answers.
AMIA ... Annual Symposium proceedings. AMIA Symposium
Mar 4, 2020
This paper describes a novel technique for annotating logical forms and answers for clinical questions by utilizing Fast Healthcare Interoperability Resources (FHIR). Such annotations are widely used in building the semantic parsing models (which aim...
Predicting Adverse Drug-Drug Interactions with Neural Embedding of Semantic Predications.
AMIA ... Annual Symposium proceedings. AMIA Symposium
Mar 4, 2020
The identification of drug-drug interactions (DDIs) is important for patient safety; yet, compared to other pharmacovigilance work, a limited amount of research has been conducted in this space. Recent work has successfully applied a method of derivi...
Clinical Tractor: A Framework for Automatic Natural Language Understanding of Clinical Practice Guidelines.
AMIA ... Annual Symposium proceedings. AMIA Symposium
Mar 4, 2020
Computational representations of the semantic knowledge embedded within clinical practice guidelines (CPGs) may be a significant aid in creating computer interpretable guidelines (CIGs). Formalizing plain text CPGs into CIGs manually is a laborious a...
Bootstrapping Adversarial Learning of Biomedical Ontology Alignments.
AMIA ... Annual Symposium proceedings. AMIA Symposium
Mar 4, 2020
Learning how to automatically align biomedical ontologies has been a long-standing goal, given their ever-growing content and the many applications that rely on them. Because the knowledge graphs underlying biomedical ontologies enable neural learnin...
Live Semantic 3D Perception for Immersive Augmented Reality.
IEEE transactions on visualization and computer graphics
Feb 13, 2020
Semantic understanding of 3D environments is critical for both the unmanned system and the human involved virtual/augmented reality (VR/AR) immersive experience. Spatially-sparse convolution, taking advantage of the intrinsic sparsity of 3D point clo...
Channel Attention Module With Multiscale Grid Average Pooling for Breast Cancer Segmentation in an Ultrasound Image.
IEEE transactions on ultrasonics, ferroelectrics, and frequency control
Feb 10, 2020
Breast cancer accounts for the second-largest number of deaths in women around the world, and more than 8% of women will suffer from the disease in their lifetime. Mortality due to breast cancer can be reduced by its early and precise diagnosis. Many...
Semantic and structural image segmentation for prosthetic vision.
PloS one
Jan 29, 2020
Prosthetic vision is being applied to partially recover the retinal stimulation of visually impaired people. However, the phosphenic images produced by the implants have very limited information bandwidth due to the poor resolution and lack of color ...
Segmentation of breast ultrasound image with semantic classification of superpixels.
Medical image analysis
Jan 25, 2020
Breast cancer is a great threat to females. Ultrasound imaging has been applied extensively in diagnosis of breast cancer. Due to the poor image quality, segmentation of breast ultrasound (BUS) image remains a very challenging task. Besides, BUS imag...
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