文献检索文档翻译深度研究
Suppr Zotero 插件Zotero 插件
邀请有礼套餐&价格历史记录

新学期,新优惠

限时优惠:9月1日-9月22日

30天高级会员仅需29元

1天体验卡首发特惠仅需5.99元

了解详情
不再提醒
插件&应用
Suppr Zotero 插件Zotero 插件浏览器插件Mac 客户端Windows 客户端微信小程序
高级版
套餐订阅购买积分包
AI 工具
文献检索文档翻译深度研究
关于我们
关于 Suppr公司介绍联系我们用户协议隐私条款
关注我们

Suppr 超能文献

核心技术专利:CN118964589B侵权必究
粤ICP备2023148730 号-1Suppr @ 2025

医学和眼科学中的自然语言处理:21 世纪临床医生的综述。

Natural Language Processing in medicine and ophthalmology: A review for the 21st-century clinician.

机构信息

Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore; Tan Tock Seng Hospital, National Healthcare Group Eye Institute, Singapore.

Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore.

出版信息

Asia Pac J Ophthalmol (Phila). 2024 Jul-Aug;13(4):100084. doi: 10.1016/j.apjo.2024.100084. Epub 2024 Jul 25.


DOI:10.1016/j.apjo.2024.100084
PMID:39059557
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11919464/
Abstract

Natural Language Processing (NLP) is a subfield of artificial intelligence that focuses on the interaction between computers and human language, enabling computers to understand, generate, and derive meaning from human language. NLP's potential applications in the medical field are extensive and vary from extracting data from Electronic Health Records -one of its most well-known and frequently exploited uses- to investigating relationships among genetics, biomarkers, drugs, and diseases for the proposal of new medications. NLP can be useful for clinical decision support, patient monitoring, or medical image analysis. Despite its vast potential, the real-world application of NLP is still limited due to various challenges and constraints, meaning that its evolution predominantly continues within the research domain. However, with the increasingly widespread use of NLP, particularly with the availability of large language models, such as ChatGPT, it is crucial for medical professionals to be aware of the status, uses, and limitations of these technologies.

摘要

自然语言处理(NLP)是人工智能的一个子领域,专注于计算机和人类语言之间的交互,使计算机能够理解、生成并从人类语言中推导含义。NLP 在医学领域的潜在应用非常广泛,从从电子健康记录中提取数据(这是其最著名和经常被利用的用途之一)到研究遗传学、生物标志物、药物和疾病之间的关系,以提出新的药物。NLP 可用于临床决策支持、患者监测或医学图像分析。尽管具有巨大的潜力,但由于各种挑战和限制,NLP 的实际应用仍然受到限制,这意味着它的发展主要仍然局限于研究领域。然而,随着 NLP 的应用越来越广泛,特别是随着大型语言模型(如 ChatGPT)的可用性,医疗专业人员了解这些技术的现状、用途和局限性至关重要。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e1a8/11919464/ec55e2477728/nihms-2064177-f0005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e1a8/11919464/6568b044d4a2/nihms-2064177-f0001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e1a8/11919464/4df83f6e25fa/nihms-2064177-f0002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e1a8/11919464/a8d3bf4695fa/nihms-2064177-f0003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e1a8/11919464/76f9153807c0/nihms-2064177-f0004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e1a8/11919464/ec55e2477728/nihms-2064177-f0005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e1a8/11919464/6568b044d4a2/nihms-2064177-f0001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e1a8/11919464/4df83f6e25fa/nihms-2064177-f0002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e1a8/11919464/a8d3bf4695fa/nihms-2064177-f0003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e1a8/11919464/76f9153807c0/nihms-2064177-f0004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e1a8/11919464/ec55e2477728/nihms-2064177-f0005.jpg

相似文献

[1]
Natural Language Processing in medicine and ophthalmology: A review for the 21st-century clinician.

Asia Pac J Ophthalmol (Phila). 2024

[2]
Natural Language Processing and Its Implications for the Future of Medication Safety: A Narrative Review of Recent Advances and Challenges.

Pharmacotherapy. 2018-7-22

[3]
The Growing Impact of Natural Language Processing in Healthcare and Public Health.

Inquiry. 2024

[4]
Deep learning-based natural language processing in ophthalmology: applications, challenges and future directions.

Curr Opin Ophthalmol. 2021-9-1

[5]
New meaning for NLP: the trials and tribulations of natural language processing with GPT-3 in ophthalmology.

Br J Ophthalmol. 2022-7

[6]
Exploring the full potential of the electronic health record: the application of natural language processing for clinical practice.

Eur J Cardiovasc Nurs. 2025-3-3

[7]
Transforming epilepsy research: A systematic review on natural language processing applications.

Epilepsia. 2023-2

[8]
Application of Natural Language Processing in Total Joint Arthroplasty: Opportunities and Challenges.

J Arthroplasty. 2023-10

[9]
Clinical Natural Language Processing for Radiation Oncology: A Review and Practical Primer.

Int J Radiat Oncol Biol Phys. 2021-7-1

[10]
Year 2023 in Biomedical Natural Language Processing: a Tribute to Large Language Models and Generative AI.

Yearb Med Inform. 2024-8

引用本文的文献

[1]
The Use of Machine Learning for Analyzing Real-World Data in Disease Prediction and Management: Systematic Review.

JMIR Med Inform. 2025-6-19

[2]
Cost-effectiveness of the 3E model in diabetes management: a machine learning approach to assess long-term economic impact.

Front Public Health. 2025-5-23

[3]
Advancing clinical biochemistry: addressing gaps and driving future innovations.

Front Med (Lausanne). 2025-4-8

本文引用的文献

[1]
Large Language Model Influence on Diagnostic Reasoning: A Randomized Clinical Trial.

JAMA Netw Open. 2024-10-1

[2]
Evaluation and mitigation of the limitations of large language models in clinical decision-making.

Nat Med. 2024-9

[3]
Residual and bidirectional LSTM for epileptic seizure detection.

Front Comput Neurosci. 2024-6-17

[4]
Identification of strains using MALDI-TOF MS combined with long short-term memory neural networks.

Aging (Albany NY). 2024-6-29

[5]
Performance of Large Language Models on Medical Oncology Examination Questions.

JAMA Netw Open. 2024-6-3

[6]
Performance of ChatGPT and Google Translate for Pediatric Discharge Instruction Translation.

Pediatrics. 2024-7-1

[7]
Utilizing Large Language Models for Enhanced Clinical Trial Matching: A Study on Automation in Patient Screening.

Cureus. 2024-5-10

[8]
Large language models in plant biology.

Trends Plant Sci. 2024-10

[9]
Use of Artificial Intelligence Chatbots in Interpretation of Pathology Reports.

JAMA Netw Open. 2024-5-1

[10]
Physician and Artificial Intelligence Chatbot Responses to Cancer Questions From Social Media.

JAMA Oncol. 2024-7-1

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

推荐工具

医学文档翻译智能文献检索