• 文献检索
  • 文档翻译
  • 深度研究
  • 学术资讯
  • Suppr Zotero 插件Zotero 插件
  • 邀请有礼
  • 套餐&价格
  • 历史记录
应用&插件
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
定价
高级版会员购买积分包购买API积分包
服务
文献检索文档翻译深度研究API 文档MCP 服务
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 @ 2026

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验

将快速医学参考(QMR)程序用作医学教育工具。

Use of the Quick Medical Reference (QMR) program as a tool for medical education.

作者信息

Miller R A, Masarie F E

出版信息

Methods Inf Med. 1989 Nov;28(4):340-5.

PMID:2695783
Abstract

The original goal of the INTERNIST-1 project, as formulated in the early 1970s, was to develop an expert consultant program for diagnosis in general internal medicine. By the early 1980s, it was recognized that the most valuable product of the project was its medical knowledge base (KB). The INTERNIST-1/QMR KB comprehensively summarizes information contained in the medical literature regarding diagnosis of disorders seen in internal medicine. The QMR program was developed to enable its users to exploit the contents of the INTERNIST-1/QMR KB in educationally, clinically, and computationally useful ways. Utilizing commonly available microcomputers, the program operates at three levels--as an electronic textbook, as an intermediate level spreadsheet for the combination and exploration of simple diagnostic concepts, and as an expert consultant program. The electronic textbook contains an average of 85 findings and 8 associated disorders relevant to the diagnosis of approximately 600 disorders in internal medicine. Inverting the disease profiles creates extensive differential diagnosis lists for the over 4250 patient findings known to the system. Unlike a standard printed medical textbook, the QMR knowledge base can be manipulated "on the fly" to format displays that match the information needs of users. Preliminary use of the program for education of medical students and medical house officers at several sites has met with an enthusiastic response.

摘要

20世纪70年代初制定的内科医生-1项目的最初目标是开发一个用于普通内科诊断的专家咨询程序。到20世纪80年代初,人们认识到该项目最有价值的产品是其医学知识库(KB)。内科医生-1/QMR知识库全面总结了医学文献中有关内科疾病诊断的信息。开发QMR程序是为了使其用户能够以在教育、临床和计算方面有用的方式利用内科医生-1/QMR知识库的内容。该程序利用常见的微型计算机,在三个层面上运行——作为一本电子教科书、作为一个用于组合和探索简单诊断概念的中级电子表格,以及作为一个专家咨询程序。这本电子教科书平均包含85项检查结果和8种相关疾病,与内科大约600种疾病的诊断有关。反转疾病概况会为系统已知的4250多项患者检查结果生成广泛的鉴别诊断列表。与标准的印刷医学教科书不同,QMR知识库可以“即时”操作,以格式化显示来匹配用户的信息需求。该程序在几个地点初步用于医学生和住院医生的教育,获得了热烈反响。

相似文献

1
Use of the Quick Medical Reference (QMR) program as a tool for medical education.将快速医学参考(QMR)程序用作医学教育工具。
Methods Inf Med. 1989 Nov;28(4):340-5.
2
The INTERNIST-1/QUICK MEDICAL REFERENCE project--status report.内科医生1号/快速医学参考项目——进展报告
West J Med. 1986 Dec;145(6):816-22.
3
An appraisal of INTERNIST-I.对内科医生决策支持系统-I的评估。
Artif Intell Med. 1995 Apr;7(2):93-116. doi: 10.1016/0933-3657(94)00028-q.
4
QUICK (QUick Index to Caduceus Knowledge): using the INTERNIST-1/CADUCEUS knowledge base as an electronic textbook of medicine.QUICK(医神知识快速索引):将内科医生-1/医神知识库用作医学电子教科书。
Comput Biomed Res. 1985 Apr;18(2):137-65. doi: 10.1016/0010-4809(85)90041-2.
5
Probabilistic diagnosis using a reformulation of the INTERNIST-1/QMR knowledge base. I. The probabilistic model and inference algorithms.使用INTERNIST-1/QMR知识库的重新表述进行概率诊断。I. 概率模型与推理算法。
Methods Inf Med. 1991 Oct;30(4):241-55.
6
Probabilistic diagnosis using a reformulation of the INTERNIST-1/QMR knowledge base. II. Evaluation of diagnostic performance.使用重新构建的内科医生-1/QMR知识库进行概率诊断。II. 诊断性能评估。
Methods Inf Med. 1991 Oct;30(4):256-67.
7
Evaluation of quick medical reference (QMR) as a teaching tool.快速医学参考(QMR)作为一种教学工具的评估。
MD Comput. 1998 Sep-Oct;15(5):323-6.
8
Effect of a computer-assisted general medicine diagnostic consultation service on housestaff diagnostic strategy.计算机辅助全科医学诊断咨询服务对住院医师诊断策略的影响。
Methods Inf Med. 1989 Nov;28(4):352-6.
9
A history of the INTERNIST-1 and Quick Medical Reference (QMR) computer-assisted diagnosis projects, with lessons learned.内科医生-1(INTERNIST-1)和快速医学参考(QMR)计算机辅助诊断项目的历史及经验教训。
Yearb Med Inform. 2010:121-36.
10
Creation of realistic appearing simulated patient cases using the INTERNIST-1/QMR knowledge base and interrelationship properties of manifestations.
Methods Inf Med. 1989 Nov;28(4):346-51.

引用本文的文献

1
Radiology Text Analysis System (RadText): Architecture and Evaluation.放射学文本分析系统(RadText):架构与评估
Proc (IEEE Int Conf Healthc Inform). 2022 Jun;2022:288-296. doi: 10.1109/ichi54592.2022.00050. Epub 2022 Sep 8.
2
Fuzzy constraint-based agent negotiation framework for doctor-patient shared decision-making.基于模糊约束的医患共同决策代理协商框架。
BMC Med Inform Decis Mak. 2022 Aug 13;22(1):218. doi: 10.1186/s12911-022-01963-x.
3
Mining Disease-Symptom Relation from Massive Biomedical Literature and Its Application in Severe Disease Diagnosis.
从海量生物医学文献中挖掘疾病-症状关系及其在重症疾病诊断中的应用
AMIA Annu Symp Proc. 2018 Dec 5;2018:1118-1126. eCollection 2018.
4
Clinical Assistant Diagnosis for Electronic Medical Record Based on Convolutional Neural Network.基于卷积神经网络的电子病历临床辅助诊断。
Sci Rep. 2018 Apr 20;8(1):6329. doi: 10.1038/s41598-018-24389-w.
5
Learning a Health Knowledge Graph from Electronic Medical Records.从电子病历中学习健康知识图谱。
Sci Rep. 2017 Jul 20;7(1):5994. doi: 10.1038/s41598-017-05778-z.
6
Clinical decision support systems in child and adolescent psychiatry: a systematic review.儿童及青少年精神病学中的临床决策支持系统:一项系统综述
Eur Child Adolesc Psychiatry. 2017 Nov;26(11):1309-1317. doi: 10.1007/s00787-017-0992-0. Epub 2017 Apr 28.
7
Compositional and enumerative designs for medical language representation.医学语言表示的成分设计与枚举设计。
Proc AMIA Annu Fall Symp. 1997:620-4.
8
Modeling principles for QMR medical findings.QMR医学发现的建模原则。
Proc AMIA Annu Fall Symp. 1996:264-8.
9
Teaching and learning methods for new generalist physicians.
J Gen Intern Med. 1994 Apr;9(4 Suppl 1):S42-9. doi: 10.1007/BF02598117.
10
Medical diagnostic decision support systems--past, present, and future: a threaded bibliography and brief commentary.医学诊断决策支持系统——过去、现在与未来:一份带注释的文献目录及简要评论
J Am Med Inform Assoc. 1994 Jan-Feb;1(1):8-27. doi: 10.1136/jamia.1994.95236141.