Article

Zero-shot extraction of seizure outcomes from clinical notes using generative pretrained transformers

2024-11-04

Abstract excerpt

<h4>Purpose</h4> Pre-trained encoder transformer models have extracted information from unstructured clinic note text but require manual annotation for supervised fine-tuning. Large, Generative Pre- trained Transformers (GPTs) may streamline this process. In this study, we explore GPTs in zero- and few-shot learning scenarios to analyze clinical health records. <h4>Materials and Methods</h4> We prompt-engineered L...

Topics

Open a Topic to create a Post that cites this publication.

Identifiers and source

Literature Corpus work: 430aed9a-d396-5aa6-8421-060243bd1794
DOI: 10.1101/2024.11.01.24316573

Open publication

Related research

Semantic proximity does not establish scientific evidence.

Click a neighbor to travelStep 1 · 12 closest

Zero-shot extraction of seizure outcomes from clinical notes using generative pretrained transformersDOI 10.1101/2024.11.01.24316573Read

Can artificial intelligence diagnose seizures based on patients’ descriptions? A study of GPT-4Semantic proximity Read

Empirical Review of LLM-driven Classification of Multidimensional Sleep Health Mentions from Free-Text Clinical NotesSemantic proximity Read

Medication information extraction using local large language modelsSemantic proximity Read

Automated epilepsy and seizure type phenotyping with pre-trained language modelsSemantic proximity Read

A Large Language Model-Based Generative Natural Language Processing Framework Finetuned on Clinical Notes Accurately Extracts Headache Frequency from Electronic Health RecordsSemantic proximity Read

clickBrick Prompt Engineering: Optimizing Large Language Model Performance in Clinical PsychiatrySemantic proximity Read

Medical text prediction and suggestion using generative pre-trained transformer models with dental medical notesSemantic proximity Read

Automated Insomnia Phenotyping from Electronic Health Records: Leveraging Large Language Models to Decode Clinical NarrativesSemantic proximity Read

A Comparative Investigation of Zero-shot Prompting and Fine-tuning for Clinical Note SummarizationSemantic proximity Read

Evaluating approaches of training a generative large language model for multi-label classification of unstructured electronic health recordsSemantic proximity Read

irAE-GPT: Leveraging large language models to identify immune-related adverse events in electronic health records and clinical trial datasetsSemantic proximity Read

Large Language Models forecast Patient Health Trajectories enabling Digital TwinsSemantic proximity Read