AIMC Topic: Semantics

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Real-time deep learning semantic segmentation during intra-operative surgery for 3D augmented reality assistance.

International journal of computer assisted radiology and surgery
PURPOSE: The current study aimed to propose a Deep Learning (DL) and Augmented Reality (AR) based solution for a in-vivo robot-assisted radical prostatectomy (RARP), to improve the precision of a published work from our group. We implemented a two-st...

Semantic Data Mining in Ubiquitous Sensing: A Survey.

Sensors (Basel, Switzerland)
Mining ubiquitous sensing data is important but also challenging, due to many factors, such as heterogeneous large-scale data that is often at various levels of abstraction. This also relates particularly to the important aspects of the explainabilit...

Behavioral correlates of cortical semantic representations modeled by word vectors.

PLoS computational biology
The quantitative modeling of semantic representations in the brain plays a key role in understanding the neural basis of semantic processing. Previous studies have demonstrated that word vectors, which were originally developed for use in the field o...

Towards Semantic Integration of Machine Vision Systems to Aid Manufacturing Event Understanding.

Sensors (Basel, Switzerland)
A manufacturing paradigm shift from conventional control pyramids to decentralized, service-oriented, and cyber-physical systems (CPSs) is taking place in today's 4th industrial revolution. Generally accepted roles and implementation recipes of cyber...

Agent-Based Semantic Role Mining for Intelligent Access Control in Multi-Domain Collaborative Applications of Smart Cities.

Sensors (Basel, Switzerland)
Significance and popularity of Role-Based Access Control (RBAC) is inevitable; however, its application is highly challenging in multi-domain collaborative smart city environments. The reason is its limitations in adapting the dynamically changing in...

HiAM: A Hierarchical Attention based Model for knowledge graph multi-hop reasoning.

Neural networks : the official journal of the International Neural Network Society
Learning to reason in large-scale knowledge graphs has attracted much attention from research communities recently. This paper targets a practical task of multi-hop reasoning in knowledge graphs, which can be applied in various downstream tasks such ...

Knowledge-Powered Deep Breast Tumor Classification With Multiple Medical Reports.

IEEE/ACM transactions on computational biology and bioinformatics
Breast tumor classification with multiple medical reports such as B-ultrasound, Mammography (X-ray) and Nuclear Magnetic Resonance Imaging (MRI) is crucial to the intelligent cancer diagnosis system. Unlike the other domain texts, the medical reports...

ILDMSF: Inferring Associations Between Long Non-Coding RNA and Disease Based on Multi-Similarity Fusion.

IEEE/ACM transactions on computational biology and bioinformatics
The dysregulation and mutation of long non-coding RNAs (lncRNAs) have been proved to result in a variety of human diseases. Identifying potential disease-related lncRNAs may benefit disease diagnosis, treatment and prognosis. A number of methods have...

A Sentence-Level Joint Relation Classification Model Based on Reinforcement Learning.

Computational intelligence and neuroscience
Relation classification is an important semantic processing task in the field of natural language processing (NLP). Data sources generally adopt remote monitoring strategies to automatically generate large-scale training data, which inevitably causes...

An Examination of the Statistical Laws of Semantic Change in Clinical Notes.

AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science
Natural language is continually changing. Given the prevalence of unstructured, free-text clinical notes in the healthcare domain, understanding the aspects of this change is of critical importance to clinical Natural Language Processing (NLP) system...