AIMC Topic: Semantics

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Sentiment analysis of classical Chinese literature: An unsupervised deep learning model with BERT and graph attention networks.

PloS one
Sentiment analysis has become a transformative technology in various contexts, particularly in Natural Language Processing (NLP), social media analytics, and literary analysis, as it can extract information from a wide range of texts. The advancement...

Detection and score grading for prostate adenocarcinoma using semantic segmentation.

PloS one
Prostate cancer is a major global health challenge. In this study, we present an approach for the detection and grading of prostate cancer through the semantic segmentation of adenocarcinoma tissues, specifically focusing on distinguishing between Gl...

Flat-Lattice-CNN: A model for Chinese medical-named-entity recognition.

PloS one
BACKGROUND: In the field of internet-based healthcare, the complexity of pathology features across various disciplines, coupled with the lack of medical training among most patients, results in medical named entities in doctor patient dialogue texts e...

From perceiving words to reading: Neural multivariate representations of sublexical vs. lexico-semantic processing during word-reading.

NeuroImage
While the neural underpinnings of semantic cognition have been extensively studied, the brain mechanisms that allow the extraction of meaning from the initially perceptual visual linguistic input are less understood. These mechanisms have typically b...

Research of text paraphrase generation based on self-contrastive learning.

PloS one
The goal of this study is to improve the quality and diversity of text paraphrase generation, a critical task in Natural Language Generation (NLG) that requires producing semantically equivalent sentences with varied structures and expressions. Exist...

GATmath and GATLc: Comprehensive benchmarks for evaluating Arabic large language models.

PloS one
The evolution of Large Language Models (LLMs) has significantly advanced artificial intelligence, driving innovation across various applications. Their continued development relies on a deep understanding of their capabilities and limitations. This i...

A prototype ETL pipeline that uses HL7 FHIR RDF resources when deploying pure functions to enrich knowledge graph patient data.

Journal of biomedical semantics
BACKGROUND: For clinical care and research, knowledge graphs with patient data can be enriched by extracting parameters from a knowledge graph and then using them as inputs to compute new patient features with pure functions. Systematic and transpare...

Enhanced glioma semantic segmentation using U-net and pre-trained backbone U-net architectures.

Scientific reports
Gliomas are known to have different sub-regions within the tumor, including the edema, necrotic, and active tumor regions. Segmenting of these regions is very important for glioma treatment decisions and management. This paper aims to demonstrate the...

Optimized AI-based neural decoding from BOLD fMRI signal for analyzing visual and semantic ROIs in the human visual system.

Journal of neural engineering
. AI-based neural decoding reconstructs visual perception by leveraging generative models to map brain activity measured through functional magnetic resonance imaging (fMRI) into the observed visual stimulus.. Traditionally, ridge linear models trans...

Natural language processing reveals network structure of pain communication in social media using discrete mathematical analysis.

Scientific reports
Pain-related discussions on social media provide valuable insights into how people naturally express and communicate their pain experiences. However, the network structure of these discussions remains poorly understood. This study analyzed 57,000 Red...