AIMC Topic: Natural Language Processing

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Evaluating the ChatGPT family of models for biomedical reasoning and classification.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: Large language models (LLMs) have shown impressive ability in biomedical question-answering, but have not been adequately investigated for more specific biomedical applications. This study investigates ChatGPT family of models (GPT-3.5, GP...

Identification and Characterization of Immune Checkpoint Inhibitor-Induced Toxicities From Electronic Health Records Using Natural Language Processing.

JCO clinical cancer informatics
PURPOSE: Immune checkpoint inhibitors (ICIs) have revolutionized cancer treatment, yet their use is associated with immune-related adverse events (irAEs). Estimating the prevalence and patient impact of these irAEs in the real-world data setting is c...

Effect of tokenization on transformers for biological sequences.

Bioinformatics (Oxford, England)
MOTIVATION: Deep-learning models are transforming biological research, including many bioinformatics and comparative genomics algorithms, such as sequence alignments, phylogenetic tree inference, and automatic classification of protein functions. Amo...

Advancing entity recognition in biomedicine via instruction tuning of large language models.

Bioinformatics (Oxford, England)
MOTIVATION: Large Language Models (LLMs) have the potential to revolutionize the field of Natural Language Processing, excelling not only in text generation and reasoning tasks but also in their ability for zero/few-shot learning, swiftly adapting to...

Surveying biomedical relation extraction: a critical examination of current datasets and the proposal of a new resource.

Briefings in bioinformatics
Natural language processing (NLP) has become an essential technique in various fields, offering a wide range of possibilities for analyzing data and developing diverse NLP tasks. In the biomedical domain, understanding the complex relationships betwe...

Effects of Language Differences on Inpatient Fall Detection Using Deep Learning.

Studies in health technology and informatics
This study examined the effects of language differences between Korean and English on the performance of natural language processing in the classification task of identifying inpatient falls from unstructured nursing notes.

Characterisation of digital therapeutic clinical trials: a systematic review with natural language processing.

The Lancet. Digital health
Digital therapeutics (DTx) are a somewhat novel class of US Food and Drug Administration-regulated software that help patients prevent, manage, or treat disease. Here, we use natural language processing to characterise registered DTx clinical trials ...