AIMC Topic: Natural Language Processing

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BioEGRE: a linguistic topology enhanced method for biomedical relation extraction based on BioELECTRA and graph pointer neural network.

BMC bioinformatics
BACKGROUND: Automatic and accurate extraction of diverse biomedical relations from literature is a crucial component of bio-medical text mining. Currently, stacking various classification networks on pre-trained language models to perform fine-tuning...

[Significance of natural language processing and chat-based generative language models].

Medizinische Klinik, Intensivmedizin und Notfallmedizin
BACKGROUND: Natural language processing (NLP) has experienced significant growth in recent years and shows potential for broad impacts in scientific research and clinical practice.

Using sequences of life-events to predict human lives.

Nature computational science
Here we represent human lives in a way that shares structural similarity to language, and we exploit this similarity to adapt natural language processing techniques to examine the evolution and predictability of human lives based on detailed event se...

Fine-tuning coreference resolution for different styles of clinical narratives.

Journal of biomedical informatics
OBJECTIVE: Coreference resolution (CR) is a natural language processing (NLP) task that is concerned with finding all expressions within a single document that refer to the same entity. This makes it crucial in supporting downstream NLP tasks such as...

Applications of natural language processing at emergency department triage: A narrative review.

PloS one
INTRODUCTION: Natural language processing (NLP) uses various computational methods to analyse and understand human language, and has been applied to data acquired at Emergency Department (ED) triage to predict various outcomes. The objective of this ...

Fusion Modeling: Combining Clinical and Imaging Data to Advance Cardiac Care.

Circulation. Cardiovascular imaging
In addition to the traditional clinical risk factors, an increasing amount of imaging biomarkers have shown value for cardiovascular risk prediction. Clinical and imaging data are captured from a variety of data sources during multiple patient encoun...

Deep learning-based natural language processing for detecting medical symptoms and histories in emergency patient triage.

The American journal of emergency medicine
OBJECTIVE: The manual recording of electronic health records (EHRs) by clinicians in the emergency department (ED) is time-consuming and challenging. In light of recent advancements in large language models (LLMs) such as GPT and BERT, this study aim...

Natural Language Processing: Chances and Challenges in Dentistry.

Journal of dentistry
INTRODUCTION: Natural language processing (NLP) is an intersection between Computer Science and Linguistic which aims to enable machines to process and understand human language. We here summarized applications and limitations of NLP in dentistry.

Artificial Intelligence Augmented Qualitative Analysis: The Way of the Future?

Qualitative health research
The artificial intelligence (AI) revolution is here and gathering momentum, thanks to new models of natural language processing (NLP) and rapidly increasing adoption by the public. NLP technology uses statistical analysis of language structures to an...

Methods for using Bing's AI-powered search engine for data extraction for a systematic review.

Research synthesis methods
Data extraction is a time-consuming and resource-intensive task in the systematic review process. Natural language processing (NLP) artificial intelligence (AI) techniques have the potential to automate data extraction saving time and resources, acce...