Literature DB >> 3620734

Knowledge engineering for a clinical trial advice system: uncovering errors in protocol specification.

M A Musen, J A Rohn, L M Fagan, E H Shortliffe.   

Abstract

ONCOCIN is an expert system that provides advice to physicians who are treating cancer patients enrolled in clinical trials. The process of encoding oncology protocol knowledge for the system has revealed serious omissions and unintentional ambiguities in the protocol documents. We have also discovered that many protocols allow for significant latitude in treating patients and that even when protocol guidelines are explicit, physicians often choose to apply their own judgment on the assumption that the specifications are incomplete. Computer-based tools offer the possibility of insuring completeness and reproducibility in the definition of new protocols. One goal of our automated protocol authoring environment, called OPAL, is to help physicians develop protocols that are free of ambiguity and thus to assure better compliance and standardization of care.

Entities:  

Mesh:

Year:  1987        PMID: 3620734

Source DB:  PubMed          Journal:  Bull Cancer        ISSN: 0007-4551            Impact factor:   1.276


  12 in total

1.  Tool support for authoring eligibility criteria for cancer trials.

Authors:  D L Rubin; J H Gennari; S Srinivas; A Yuen; H Kaizer; M A Musen; J S Silva
Journal:  Proc AMIA Symp       Date:  1999

2.  Analysis of the practice guidelines of the Dutch College of General Practitioners with respect to the use of blood tests.

Authors:  M A van Wijk; A M Bohnen; J van der Lei
Journal:  J Am Med Inform Assoc       Date:  1999 Jul-Aug       Impact factor: 4.497

3.  Knowledge representation and tool support for critiquing clinical trial protocols.

Authors:  D L Rubin; J Gennari; M A Musen
Journal:  Proc AMIA Symp       Date:  2000

4.  Correlating eligibility criteria generalizability and adverse events using Big Data for patients and clinical trials.

Authors:  Anando Sen; Patrick B Ryan; Andrew Goldstein; Shreya Chakrabarti; Shuang Wang; Eileen Koski; Chunhua Weng
Journal:  Ann N Y Acad Sci       Date:  2016-09-06       Impact factor: 5.691

5.  GIST 2.0: A scalable multi-trait metric for quantifying population representativeness of individual clinical studies.

Authors:  Anando Sen; Shreya Chakrabarti; Andrew Goldstein; Shuang Wang; Patrick B Ryan; Chunhua Weng
Journal:  J Biomed Inform       Date:  2016-09-04       Impact factor: 6.317

6.  Trend and Network Analysis of Common Eligibility Features for Cancer Trials in ClinicalTrials.gov.

Authors:  Chunhua Weng; Anil Yaman; Kuo Lin; Zhe He
Journal:  Smart Health (2014)       Date:  2014-07

7.  T-HELPER: automated support for community-based clinical research.

Authors:  M A Musen; R W Carlson; L M Fagan; S C Deresinski; E H Shortliffe
Journal:  Proc Annu Symp Comput Appl Med Care       Date:  1992

8.  Optimizing Clinical Research Participant Selection with Informatics.

Authors:  Chunhua Weng
Journal:  Trends Pharmacol Sci       Date:  2015-11       Impact factor: 14.819

9.  The guideline interchange format: a model for representing guidelines.

Authors:  L Ohno-Machado; J H Gennari; S N Murphy; N L Jain; S W Tu; D E Oliver; E Pattison-Gordon; R A Greenes; E H Shortliffe; G O Barnett
Journal:  J Am Med Inform Assoc       Date:  1998 Jul-Aug       Impact factor: 4.497

10.  A knowledge base of clinical trial eligibility criteria.

Authors:  Hao Liu; Yuan Chi; Alex Butler; Yingcheng Sun; Chunhua Weng
Journal:  J Biomed Inform       Date:  2021-04-01       Impact factor: 6.317

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.