Computer-aided disease prediction system: Development of application software with SAS component language

Chi Ming Chang, Hsu Sung Kuo, Shu Hui Chang, Hong Jen Chang, Der Ming Liou, Tabar Laszlo, Tony Hsiu Hsi Chen

Research output: Contribution to journalArticlepeer-review

8 Citations (Scopus)


Aims: The intricacy of predictive models associated with prognosis and risk classification of disease often discourages medical personnel who are interested in this field. The aim of this study was therefore to develop a computer-aided disease prediction model underpinning a step-by-step statistics-guided approach including five components: (1) data management; (2) exploratory analysis; (3) type of predictive model; (4) model verification; (5) interactive mode of disease prediction using SAS 8.02 Windows 2000 as a platform. Methods: The application of this system was illustrated by using data from the Swedish Two-County Trial on breast cancer screening. The effects of tumour size, node status, and histological grade on breast cancer death using logistic regression model or survival models were predicted. A total of 20 questions were designed to exemplify the usefulness of each component. We also evaluated the system using a controlled randomized trial. Times to finish the above 20 questions were used as endpoint to evaluate the performance of the current system. User satisfaction with the current system such as easy to use, the efficiency of risk prediction, and the reduction of barrier to predictive model was also evaluated. Results: The intervention group not only performed more efficiently than the control group but also satisfied with this application software. Conclusions: The MD-DP-SOS system characterized by menu-driven style, comprehensiveness, accuracy and adequacy assessment, and interactive mode of disease prediction is helpful for medical personnel who are involved in disease prediction.

Original languageEnglish
Pages (from-to)139-159
Number of pages21
JournalJournal of Evaluation in Clinical Practice
Issue number2
Publication statusPublished - Apr 1 2005
Externally publishedYes


  • Computer-aided system
  • Cox regression model
  • Disease prediction model
  • Logistic regression
  • Randomized control trial
  • SAS software
  • Survival model

ASJC Scopus subject areas

  • Health Policy
  • Public Health, Environmental and Occupational Health


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