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Natural Language Processing

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An automated framework for assessing how well LLMs cite relevant medical references.

Nature communications
As large language models (LLMs) are increasingly used to address health-related queries, it is crucial that they support their conclusions with credible references. While models can cite sources, the extent to which these support claims remains uncle...

Empowering entity synonym set generation using flexible perceptual field and multi-layer contextual information.

PloS one
Automatic generation of entity synonyms plays a pivotal role in various natural language processing applications, such as search engines, question-answering systems, and taxonomy construction. Previous research on generating entity synonym sets has t...

Exploring the Potential of Non-Proprietary Language Models for Analysing Patient-Reported Experiences.

Studies in health technology and informatics
Large language models (LLMs) are increasingly being explored for various applications in medical language processing. Due to data privacy issues, it is recommended to apply non-proprietary models that can be run locally. Therefore, this study aims to...

Industrial applications of large language models.

Scientific reports
Large language models (LLMs) are artificial intelligence (AI) based computational models designed to understand and generate human like text. With billions of training parameters, LLMs excel in identifying intricate language patterns, enabling remark...

Engaging Stakeholders With Professional or Lived Experience to Improve Firearm Violence Lexicon Development.

JMIR formative research
Framing the public health burden of firearm violence should include people with secondary exposure to firearm violence beyond acute bodily injury, yet such data are limited. Electronic health record clinical notes, when leveraged through natural lang...

Hierarchical embedding attention for overall survival prediction in lung cancer from unstructured EHRs.

BMC medical informatics and decision making
The automated processing of Electronic Health Records (EHRs) poses a significant challenge due to their unstructured nature, rich in valuable, yet disorganized information. Natural Language Processing (NLP), particularly Named Entity Recognition (NER...

Arch-Eval benchmark for assessing chinese architectural domain knowledge in large language models.

Scientific reports
The burgeoning application of Large Language Models (LLMs) in Natural Language Processing (NLP) has prompted scrutiny of their domain-specific knowledge processing, especially in the construction industry. Despite high demand, there is a scarcity of ...

Dual-channel knowledge attention for traditional Chinese medicine syndrome differentiation.

Scientific reports
With the rapid advancement of Natural Language Processing (NLP) technologies, the application of NLP to enable intelligent syndrome differentiation in Traditional Chinese Medicine (TCM) has become a popular research focus. However, TCM texts contain ...

Decoding Recurrence in Early-Stage and Locoregionally Advanced Non-Small Cell Lung Cancer: Insights From Electronic Health Records and Natural Language Processing.

JCO clinical cancer informatics
PURPOSE: Recurrences after curative resection in early-stage and locoregionally advanced non-small cell lung cancer (NSCLC) are common, necessitating a nuanced understanding of associated risk factors. This study aimed to establish a natural language...

GDReCo: Fine-grained gene-disease relationship extraction corpus.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Understanding gene-disease relationships is crucial for medical research, drug discovery, clinical diagnosis, and other fields. However, there is currently no high-quality, fine-grained corpus available for training Natural ...