User satisfaction with a smartphone-compatible, artificial intelligence-based cutaneous pigmented lesion evaluator

Yen Po (Harvey) Chin, I. Hsin Huang, Ze Yu Hou, Po Yu Chen, Fatima Bassir, Hsiao Han Wang, Yu Ting Lin, Yu Chuan (Jack) Li

Research output: Contribution to journalArticlepeer-review

5 Citations (Scopus)


Introduction: Melanoma is the most aggressive type of skin cancer, and it may arise from a cutaneous pigmented lesion. As artificial intelligence (AI)-based teledermatology services hold promise in redefining the melanoma screening paradigm, a study that evaluates user satisfaction with a smartphone-compatible, AI-based cutaneous pigmented lesion evaluator is lacking. Methods: Data was collected between April and May 2019 in Taiwan. To assess user satisfaction with MoleMe, an AI-based cutaneous pigmented lesion evaluator on a smartphone, users were asked to complete a questionnaire designed to evaluate four aspects, including interaction, impact on daily life, usability, and overall performance, after completing a MoleMe evaluation session. For each question, users could rank their satisfaction level from 1 to 5, with five showing strongly satisfied and one showing strongly unsatisfied. The Kruskal-Wallis and Wilcoxon rank-sum tests were used to compare user satisfaction among different age groups, genders, and risk predictions received. Result: A total of 1231 questionnaires were collected for analysis. Over 90% of the participants were satisfied (score = 4 or 5) and over 75% of the participants were strongly satisfied (score 5) with MoleMe, in terms of usability, interaction, and impact on daily life. The user satisfaction did not show a significant difference between genders, age groups, and risk predictions received. (all P > 0.05) Conclusion: With high user satisfaction regardless of age group, gender, and risk prediction received, AI-based teledermatology services on a smartphone such as MoleMe may potentially achieve widespread usage and be beneficial to both patients and physicians.

Original languageEnglish
Article number105649
Pages (from-to)105649
JournalComputer Methods and Programs in Biomedicine
Publication statusPublished - Oct 2020


  • Artificial intelligence
  • Deep learning
  • Melanoma
  • Pigmented cutaneous lesion
  • Teledermatology
  • User satisfaction

ASJC Scopus subject areas

  • Software
  • Computer Science Applications
  • Health Informatics


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