AIMC Topic: Natural Language Processing
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A textual dataset of de-identified health records in Spanish and Catalan for medical entity recognition and anonymization.
Scientific data
Jul 1, 2025
The advancement of clinical natural language processing systems is crucial to exploit the wealth of textual data contained in medical records. Diverse data sources are required in different languages and from different sites to represent global healt...
Analyzing Patient Complaints in Web-Based Reviews of Private Hospitals in Selangor, Malaysia, Using Large Language Model-Assisted Content Analysis: Mixed Methods Study.
JMIR formative research
Jun 27, 2025
BACKGROUND: Large language model (LLM)-assisted content analysis (LACA) is a modification of traditional content analysis, leveraging the LLM to codevelop codebooks and automatically assign thematic codes to a web-based reviews dataset.
Text intelligent correction in English translation: A study on integrating models with dependency attention mechanism.
PloS one
Jun 24, 2025
Improving translation quality and efficiency is one of the key challenges in the field of Natural Language Processing (NLP). This study proposes an enhanced model based on Bidirectional Encoder Representations from Transformers (BERT), combined with ...
Text speaks louder: Insights into personality from natural language processing.
PloS one
Jun 18, 2025
In recent years, advancements in natural language processing (NLP) have enabled new approaches to personality assessment. This article presents an interdisciplinary investigation that leverages explainable AI techniques, particularly Integrated Gradi...
Classifying Stereotactic Radiosurgery Patients by Primary Diagnosis Using Natural Language Processing of Clinical Notes.
JCO clinical cancer informatics
Jun 13, 2025
PURPOSE: Accurate identification of the primary tumor diagnosis of patients who have undergone stereotactic radiosurgery (SRS) from electronic health records is a critical but challenging task. Traditional methods of identifying the primary tumor his...
Enhancing Pulmonary Disease Prediction Using Large Language Models With Feature Summarization and Hybrid Retrieval-Augmented Generation: Multicenter Methodological Study Based on Radiology Report.
Journal of medical Internet research
Jun 11, 2025
BACKGROUND: The rapid advancements in natural language processing, particularly the development of large language models (LLMs), have opened new avenues for managing complex clinical text data. However, the inherent complexity and specificity of medi...
Chinese medical named entity recognition based on multimodal information fusion and hybrid attention mechanism.
PloS one
Jun 11, 2025
Chinese Medical Named Entity Recognition (CMNER) seeks to identify and extract medical entities from unstructured medical texts. Existing methods often depend on single-modality representations and fail to fully exploit the complementary nature of di...
First impressions of a humanoid social robot with natural language capabilities.
Scientific reports
Jun 5, 2025
Concurrent developments in robotic design and natural language processing (NLP) have enabled the production of humanoid chatbots that can operate in commercial and community settings. Though still novel, the presence of physically embodied social rob...
Analyzing the evolutionary trajectory of technological themes based on the BERTopic model: A case study in the field of artificial intelligence.
PloS one
Jun 5, 2025
As the wave of technological innovation propels national development into the future, technological advancement has emerged as a crucial pillar for enhancing international competitiveness. Unraveling the evolutionary trajectory of technologies and th...
Use of deep learning-based NLP models for full-text data elements extraction for systematic literature review tasks.
Scientific reports
Jun 3, 2025
Systematic literature review (SLR) is an important tool for Health Economics and Outcomes Research (HEOR) evidence synthesis. SLRs involve the identification and selection of pertinent publications and extraction of relevant data elements from full-t...
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