AIMC Topic: Semantics

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Composition as Nonlinear Combination in Semantic Space: A Computational Characterization of Compound Processing.

Cognitive science
Most Chinese words are compounds formed through the combination of meaningful characters. Yet, due to compositional complexity, it is poorly understood how this combinatorial process affects the access to the whole-word meaning. In the present study,...

Identifying stigmatizing and positive/preferred language in obstetric clinical notes using natural language processing.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: To identify stigmatizing language in obstetric clinical notes using natural language processing (NLP).

TP-RotatE: A knowledge graph representation learning method combining path information and rules to capture complex relational patterns.

PloS one
Representation learning on a knowledge graph (KG) aims to map entities and relationships into a low-dimensional vector space. Traditional methods for representation learning have predominantly focused on the structural aspects of triples within the K...

Research on autonomous obstacle avoidance of mountainous tractors based on semantic neural network and laser SLAM.

PloS one
The accuracy and consistency of obstacle avoidance map construction are poor in complex and changeable dynamic environment. In order to improve the driving safety of mountain tractors in complex mountain environment, an autonomous obstacle avoidance ...

Deep learning based semantic segmentation of leukemia effected white blood cell.

PloS one
Medical image segmentation has numerous applications in diagnosing different diseases. Various types of diseases are found in white blood and Red blood cells. This paper represents the segmentation of WBCs from blood smear images. It is a complex and...

Semantic abnormalities in schizophrenia and bipolar disorder: A natural language processing approach.

Science progress
INTRODUCTION: The diagnostic boundaries between schizophrenia and bipolar disorder are controversial due to the ambiguity of psychiatric nosology. From this perspective, it is noteworthy that formal thought disorder has historically been considered p...

JTIS: enhancing biomedical document-level relation extraction through joint training with intermediate steps.

Database : the journal of biological databases and curation
Biomedical Relation Extraction (RE) is central to Biomedical Natural Language Processing and is crucial for various downstream applications. Existing RE challenges in the field of biology have primarily focused on intra-sentential analysis. However, ...

BioGSF: a graph-driven semantic feature integration framework for biomedical relation extraction.

Briefings in bioinformatics
The automatic and accurate extraction of diverse biomedical relations from literature constitutes the core elements of medical knowledge graphs, which are indispensable for healthcare artificial intelligence. Currently, fine-tuning through stacking v...

Enhancing Arden-Syntax-Based Clinical Reasoning with Ontologies.

Studies in health technology and informatics
We present a new methodological approach based on integrating Arden-Syntax-based clinical decision support (CDS) with an upstream ontology service. Incoming linguistic patient data, such as single reports about detected germs or viruses, shall be ide...

FHIR-Based Arden Syntax Compiler for Clinical Decision Support.

Studies in health technology and informatics
The Arden Syntax is a language designed for the encoding of medical knowledge into clinical decision support systems. Its evolution is overseen by Health Level 7. A significant enhancement in its new version 3.0 is the incorporation of FHIR for data ...