Building a patient oriented treatment decision system for liver cancer

Cheng Mei Chen, Chien-Yeh Hsu, Chyi Huey Bai

Research output: Chapter in Book/Report/Conference proceedingConference contribution

5 Citations (Scopus)


The aim of this study is to establish a decision system to assist liver cancer patients to choose treatments, and explore whether patients' treatment preferences were concordant with their physicians' recommendations. We analyzed the patients' considerations involved in the evaluation of treatment and combined these considerations with Barcelona Clinic Liver Cancer (BCLC) clinical guidelines to design the surveys and adopted Multi-Attribute Utility Theory (MAUT) to establish a decision model for treatment selections. Without intervening the clinical processes, we interviewed 53 liver cancer patients(and their families) using this decision system to choose preferred treatments. The results showed: (1) There was a difference between liver cancer patients' treatment preferences and their physicians' recommendations; (2) Liver cancer patients with advanced stage, still prefer active treatment; (3) The most concerns on treatments were cure rate, survival rate and self-care ability. Instead of only following physicians' recommendations, this system assist liver cancer patients to evaluate treatment using various factors(considerations) including physiological, psychological and social support. For oncologists, we suggest the psychological processes of patients are taken into consideration, and this study provide an example of framework on cancer care interventions and expect to improve the care of liver cancer population in the future.

Original languageEnglish
Title of host publicationProceedings - 2012 3rd Global Congress on Intelligent Systems, GCIS 2012
Number of pages6
Publication statusPublished - 2012
Event2012 3rd Global Congress on Intelligent Systems, GCIS 2012 - Wuhan, China
Duration: Nov 6 2012Nov 8 2012


Other2012 3rd Global Congress on Intelligent Systems, GCIS 2012


  • BCLC
  • Decision support
  • Liver cancer
  • MAUT
  • Treatment

ASJC Scopus subject areas

  • Artificial Intelligence
  • Information Systems


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