Literature DB >> 23304392

Automated illustration of patients instructions.

Duy Bui1, Carlos Nakamura, Bruce E Bray, Qing Zeng-Treitler.   

Abstract

A picture can be a powerful communication tool. However, creating pictures to illustrate patient instructions can be a costly and time-consuming task. Building on our prior research in this area, we developed a computer application that automatically converts text to pictures using natural language processing and computer graphics techniques. After iterative testing, the automated illustration system was evaluated using 49 previously unseen cardiology discharge instructions. The completeness of the system-generated illustrations was assessed by three raters using a three-level scale. The average inter-rater agreement for text correctly represented in the pictograph was about 66 percent. Since illustration in this context is intended to enhance rather than replace text, these results support the feasibility of conducting automated illustration.

Entities:  

Mesh:

Year:  2012        PMID: 23304392      PMCID: PMC3540454     

Source DB:  PubMed          Journal:  AMIA Annu Symp Proc        ISSN: 1559-4076


  22 in total

1.  Aggregating UMLS semantic types for reducing conceptual complexity.

Authors:  A T McCray; A Burgun; O Bodenreider
Journal:  Stud Health Technol Inform       Date:  2001

2.  UMLS language and vocabulary tools.

Authors:  Allen C Browne; Guy Divita; Alan R Aronson; Alexa T McCray
Journal:  AMIA Annu Symp Proc       Date:  2003

3.  A Taxonomy of Representation Strategies in Iconic Communication.

Authors:  Carlos Nakamura; Qing Zeng-Treitler
Journal:  Int J Hum Comput Stud       Date:  2012-03-23       Impact factor: 3.632

4.  FDA electronic drug labels to improve patient safety.

Authors: 
Journal:  J Pain Palliat Care Pharmacother       Date:  2006

5.  Pictures and text in instructions for medical devices: effects on recall and actual performance.

Authors:  Marieke Kools; Margaretha W J van de Wiel; Robert A C Ruiter; Gerjo Kok
Journal:  Patient Educ Couns       Date:  2006-02-10

6.  Patient comprehension of doctor-patient communication on discharge from the emergency department.

Authors:  J A Crane
Journal:  J Emerg Med       Date:  1997 Jan-Feb       Impact factor: 1.484

7.  Using pictographs to enhance recall of spoken medical instructions.

Authors:  P S Houts; R Bachrach; J T Witmer; C A Tringali; J A Bucher; R A Localio
Journal:  Patient Educ Couns       Date:  1998-10

8.  The use of illustrations and narrative text style to improve readability of a health education brochure.

Authors:  R Michielutte; J Bahnson; M B Dignan; E M Schroeder
Journal:  J Cancer Educ       Date:  1992       Impact factor: 2.037

9.  Development of an illustrated medication schedule as a low-literacy patient education tool.

Authors:  Sunil Kripalani; Rashanda Robertson; Melissa H Love-Ghaffari; Laura E Henderson; Jessica Praska; Akilah Strawder; Marra G Katz; Terry A Jacobson
Journal:  Patient Educ Couns       Date:  2007-03-06

10.  Assessment of pictographs developed through a participatory design process using an online survey tool.

Authors:  Hyeoneui Kim; Carlos Nakamura; Qing Zeng-Treitler
Journal:  J Med Internet Res       Date:  2009-02-24       Impact factor: 5.428

View more
  7 in total

1.  Low Literacy Level Instructions and Reminder Calls Improve Patient Handling of Fecal Immunochemical Test Samples.

Authors:  Andrew Wang; Carly Rachocki; Jean A Shapiro; Rachel B Issaka; Ma Somsouk
Journal:  Clin Gastroenterol Hepatol       Date:  2018-11-29       Impact factor: 11.382

2.  Doodle Health: A Crowdsourcing Game for the Co-design and Testing of Pictographs to Reduce Disparities in Healthcare Communication.

Authors:  Carrie Christensen; Doug Redd; Erica Lake; Jean P Shipman; Heather Aiono; Roger Altizer; Bruce E Bray; Qing T Zeng
Journal:  AMIA Annu Symp Proc       Date:  2018-04-16

3.  Automated pictographic illustration of discharge instructions with Glyph: impact on patient recall and satisfaction.

Authors:  Brent Hill; Seneca Perri-Moore; Jinqiu Kuang; Bruce E Bray; Long Ngo; Alexa Doig; Qing Zeng-Treitler
Journal:  J Am Med Inform Assoc       Date:  2016-05-27       Impact factor: 4.497

4.  Evaluation of a pictograph enhancement system for patient instruction: a recall study.

Authors:  Qing Zeng-Treitler; Seneca Perri; Carlos Nakamura; Jinqiu Kuang; Brent Hill; Duy Duc An Bui; Gregory J Stoddard; Bruce E Bray
Journal:  J Am Med Inform Assoc       Date:  2014-06-12       Impact factor: 4.497

5.  Crowdsourcing participatory evaluation of medical pictograms using Amazon Mechanical Turk.

Authors:  Bei Yu; Matt Willis; Peiyuan Sun; Jun Wang
Journal:  J Med Internet Res       Date:  2013-06-03       Impact factor: 5.428

6.  Assessing Pictograph Recognition: A Comparison of Crowdsourcing and Traditional Survey Approaches.

Authors:  Jinqiu Kuang; Lauren Argo; Greg Stoddard; Bruce E Bray; Qing Zeng-Treitler
Journal:  J Med Internet Res       Date:  2015-12-17       Impact factor: 5.428

7.  Automatic and intelligent content visualization system based on deep learning and genetic algorithm.

Authors:  Murat İnce
Journal:  Neural Comput Appl       Date:  2022-01-15       Impact factor: 5.606

  7 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.