Natural Language Generation in Healthcare: A Review of Methods and Applications
Natural language generation (NLG) is the key technology to achieve generative artificial intelligence (AI). With the breakthroughs in large language models (LLMs), NLG has been widely used in various medical applications, demonstrating the potential to enhance clinical workflows, support clinical decision-making, and improve clinical documentation. Heterogeneous and diverse medical data modalities, such as medical text, images, and knowledge bases, are utilized in NLG. Researchers have proposed many generative models and applied them in a number of healthcare applications. There is a need for a comprehensive review of NLG methods and applications in the medical domain. In this study, we systematically reviewed 113 scientific publications from a total of 3,988 NLG-related articles identified using a literature search, focusing on data modality, model architecture, clinical applications, and evaluation methods. Following PRISMA (Preferred Reporting Items for Systematic reviews and Meta-Analyses) guidelines, we categorize key methods, identify clinical applications, and assess their capabilities, limitations, and emerging challenges. This timely review covers the key NLG technologies and medical applications and provides valuable insights for future studies to leverage NLG to transform medical discovery and healthcare.
Code (0)
등록된 구현이 없습니다.
Tasks
ArticlesDecision MakingText GenerationSimilar Papers 제목 키워드 기반
Vision-Language Models for Medical Report Generation and Visual Question Answering: A Review
Medical vision-language models (VLMs) combine computer vision (CV) and natural language processing (NLP) to analyze visual and textual medical data. Our paper reviews recent advancements in developing VLMs specialized fo…
Medical Report GenerationQuestion AnsweringVisual Question AnsweringVisual Question Answering (VQA)Prompt Engineering for Healthcare: Methodologies and Applications
Prompt engineering is a critical technique in the field of natural language processing that involves designing and optimizing the prompts used to input information into models, aiming to enhance their performance on spec…
Machine TranslationPrompt EngineeringQuestion AnsweringText Summarization+1Neural Natural Language Processing for Unstructured Data in Electronic Health Records: a Review
Electronic health records (EHRs), digital collections of patient healthcare events and observations, are ubiquitous in medicine and critical to healthcare delivery, operations, and research. Despite this central role, EH…
Knowledge GraphsQuestion AnsweringWord EmbeddingsThe Role of Language Models in Modern Healthcare: A Comprehensive Review
The application of large language models (LLMs) in healthcare has gained significant attention due to their ability to process complex medical data and provide insights for clinical decision-making. These models have dem…
Decision MakingA Review of Reinforcement Learning for Natural Language Processing, and Applications in Healthcare
Reinforcement learning (RL) has emerged as a powerful approach for tackling complex medical decision-making problems such as treatment planning, personalized medicine, and optimizing the scheduling of surgeries and appoi…
Decision MakingMachine TranslationQuestion AnsweringReinforcement Learning (RL)+3