AIMC Topic: Natural Language Processing
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Comparing traditional natural language processing and large language models for mental health status classification: a multi-model evaluation.
Scientific reports
Jul 6, 2025
The substantial increase in mental health disorders globally necessitates scalable, accurate tools for detecting and classifying these conditions in digital environments. This study addresses the critical challenge of automated mental health classifi...
Leveraging heterogeneous tabular of EHRs with prompt learning for clinical prediction.
Journal of biomedical informatics
Jul 4, 2025
Electronic Health Records (EHRs) depict patient-related information and have significantly contributed to advancements in healthcare fields. The abundance of EHR data provides exceptional opportunities for developing clinical predictive models. Howev...
Fine-tuning of language models for automated structuring of medical exam reports to improve patient screening and analysis.
Scientific reports
Jul 4, 2025
The analysis of medical imaging reports is labour-intensive but crucial for accurate diagnosis and effective patient screening. Often presented as unstructured text, these reports require systematic organisation for efficient interpretation. This stu...
Keyword-optimized template insertion for clinical note classification via prompt-based learning.
BMC medical informatics and decision making
Jul 3, 2025
BACKGROUND: Prompt-based learning involves the additions of prompts (i.e., templates) to the input of pre-trained large language models (PLMs) to adapt them to specific tasks with minimal training. This technique is particularly advantageous in clini...
Predicting RNA Structure Utilizing Attention from Pretrained Language Models.
Journal of chemical information and modeling
Jul 2, 2025
RNA possesses functional significance that extends beyond the transport of genetic information. The functional roles of noncoding RNA can be mediated through their tertiary and secondary structure, and thus, predicting RNA structure holds great promi...
Particle swarm optimization-based NLP methods for optimizing automatic document classification and retrieval.
PloS one
Jul 2, 2025
Text classification plays an essential role in natural language processing and is commonly used in tasks like categorizing news, sentiment analysis, and retrieving relevant information. [0pc][-9pc]Please check and confirm the inserted city and countr...
Exploring the possibilities and limitations of customized large language model to support and improve cervical cancer screening.
BMC medical informatics and decision making
Jul 1, 2025
BACKGROUND: The rapid advancement of artificial intelligence, driven by Generative Pre-trained Transformers (GPT), has transformed natural language processing. Prompt engineering plays a key role in guiding model outputs effectively. Our primary obje...
An explainable RoBERTa approach to analyzing panic and anxiety sentiment in oral health education YouTube comments.
Scientific reports
Jul 1, 2025
Online videos are vital for health education and medical decision-making, but their comment sections often spread misinformation, causing anxiety and confusion. This study identifies stress-inducing comments in oral health education content, aiming t...
Sentiment classification for telugu using transformed based approaches on a multi-domain dataset.
Scientific reports
Jul 1, 2025
Sentiment analysis is an essential component of Natural Language Processing (NLP) in resource-abundant languages such as English. Nevertheless, poor-resource languages such as Telugu have experienced limited efforts owing to multiple considerations, ...
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...
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