AIMC Topic: Semantics

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TGAP-Net: Twin Graph Attention Pseudo-Label Generation for Weakly Supervised Semantic Segmentation.

IEEE journal of biomedical and health informatics
Multilabel pathological tissue segmentation is a vital task in computational pathology that aims to semantically segment different tissues within pathological images. Fully and weakly supervised models have demonstrated impressive performances in thi...

Improvement of metaphor understanding via a cognitive linguistic model based on hierarchical classification and artificial intelligence SVM.

Scientific reports
This study aims to enhance computers' ability to understand and generate metaphors, offering a novel perspective and technical approach in the field of natural language processing. It proposes a metaphor recognition algorithm that combines a Convolut...

A novel approach for multiclass sentiment analysis on Chinese social media with ERNIE-MCBMA.

Scientific reports
Weibo, one of the most widely used social media platforms in China, sees a vast number of users expressing their opinions and emotional tendencies. Conducting sentiment analysis on Weibo posts using natural language processing techniques is crucial f...

Multi-Knowledge Graph and Multi-View Entity Feature Learning for Predicting Drug-Related Side Effects.

Journal of chemical information and modeling
Computational prediction of potential drug side effects plays a crucial role in reducing health risks for clinical patients and accelerating drug development. Recent methods have constructed heterogeneous graphs that represent drugs and their side ef...

Unveiling differential adverse event profiles in vaccines via LLM text embeddings and ontology semantic analysis.

Journal of biomedical semantics
BACKGROUND: Vaccines are crucial for preventing infectious diseases; however, they may also be associated with adverse events (AEs). Conventional analysis of vaccine AEs relies on manual review and assignment of AEs to terms in terminology or ontolog...

Towards Semantic Interoperability Health Standardization Recommendation Tool.

Studies in health technology and informatics
The European Rolling Plan for ICT Standardization outlines activities that connect EU policies to standardization efforts in different technological domains. Artificial Intelligence (AI), security, and cybersecurity are at the top of the agenda of th...

Efficient Semantic Similarity Computing with Optimized BERT Models.

Studies in health technology and informatics
Bridging diverse terminologies and ensuring precise information retrieval, semantic similarity in medical language is key to improve healthcare outcomes. Semantic similarity measures how closely pieces of text share the same meaning, a crucial elemen...

Assessing the Potential of an LLM-Powered System for Enhancing FHIR Resource Validation.

Studies in health technology and informatics
Large Language Models (LLMs) have gained significant popularity among healthcare professionals as tools for AI-driven interactions. These models can analyze large volumes of clinical data, including patient narratives, to assist in efficient decision...

Towards the Common Data Model for an Intensive Medicine Data Space in Europe.

Studies in health technology and informatics
This work aims to identify the Key Research Areas for building and deploying the semantic interoperability framework for the Intensive Medicine Data Space in Europe. A set of European experts defined four research areas and associated challenges: i) ...

Validating Hierarchical Alignments of Partially Antonymous Concept Pairs in SNOMED CT.

Studies in health technology and informatics
SNOMED CT is a comprehensive controlled biomedical ontology widely used as an information exchange standard among various healthcare institutions. To ensure the unambiguous expression of health data and effective linguistic computation of word meanin...