A sco** review of using large language models (LLMs) to investigate electronic health records (EHRs)
Prompt engineering for healthcare: Methodologies and applications
J Wang, E Shi, S Yu, Z Wu, C Ma, H Dai, Q Yang… - ar** of postpartum hemorrhage using large language models
E Alsentzer, MJ Rasmussen, R Fontoura, AL Cull… - NPJ Digital …, 2023 - nature.com
Many areas of medicine would benefit from deeper, more accurate phenoty**, but there
are limited approaches for phenoty** using clinical notes without substantial annotated …
are limited approaches for phenoty** using clinical notes without substantial annotated …
[HTML][HTML] Cpllm: Clinical prediction with large language models
We present Clinical Prediction with Large Language Models (CPLLM), a method that
involves fine-tuning a pre-trained Large Language Model (LLM) for predicting clinical …
involves fine-tuning a pre-trained Large Language Model (LLM) for predicting clinical …
Ensuring useful adoption of generative artificial intelligence in healthcare
Objectives This article aims to examine how generative artificial intelligence (AI) can be
adopted with the most value in health systems, in response to the Executive Order on AI …
adopted with the most value in health systems, in response to the Executive Order on AI …
Clinical prompt learning with frozen language models
When the first transformer-based language models were published in the late 2010s,
pretraining with general text and then fine-tuning the model on a task-specific dataset often …
pretraining with general text and then fine-tuning the model on a task-specific dataset often …
[HTML][HTML] MED-Prompt: A novel prompt engineering framework for medicine prediction on free-text clinical notes
Existing AI-based medicine prediction systems require substantial training time, computing
resources, and extensive labeled data, yet they often lack scalability. To bridge these gaps …
resources, and extensive labeled data, yet they often lack scalability. To bridge these gaps …
Multi-Label few-shot ICD coding as autoregressive generation with prompt
Abstract Automatic International Classification of Diseases (ICD) coding aims to assign
multiple ICD codes to a medical note with an average of 3,000+ tokens. This task is …
multiple ICD codes to a medical note with an average of 3,000+ tokens. This task is …