An iPhone application using a novel stool color detection algorithm for biliary atresia screening

Eri Hoshino, Kuniyoshi Hayashi, Mitsuyoshi Suzuki, Masayuki Obatake, Kevin Y. Urayama, Satoshi Nakano, Yasuyuki Taura, Masaki Nio, Osamu Takahashi

Research output: Contribution to journalArticle

5 Citations (Scopus)

Abstract

Background: The stool color card has been the primary tool for identifying acholic stools in infants with biliary atresia (BA), in several countries. However, BA stools are not always acholic, as obliteration of the bile duct occurs gradually. This study aims to introduce Baby Poop (Baby unchi in Japanese), a free iPhone application, employing a detection algorithm to capture subtle differences in colors, even with non-acholic BA stools. Methods: The application is designed for use by caregivers of infants aged approximately 2 weeks–1 month. Baseline analysis to determine optimal color parameters predicting BA stools was performed using logistic regression (n = 50). Pattern recognition and machine learning processes were performed using 30 BA and 34 non-BA images. Additional 5 BA and 35 non-BA pictures were used to test accuracy. Results: Hue, saturation, and value (HSV) were the preferred parameter for BA stool identification. A sensitivity and specificity were 100% (95% confidence interval 0.48–1.00 and 0.90–1.00, respectively) even among a collection of visually non-acholic, i.e., pigmented BA stools and relatively pale-colored non-BA stools. Conclusions: Results suggest that an iPhone mobile application integrated with a detection algorithm is an effective and convenient modality for early detection of BA, and potentially for other related diseases.

Original languageEnglish
Pages (from-to)1115-1121
Number of pages7
JournalPediatric Surgery International
Volume33
Issue number10
DOIs
Publication statusPublished - 2017 Oct 1

Keywords

  • Biliary atresia
  • Detection algorithm
  • Screening
  • Stool color
  • iPhone application

ASJC Scopus subject areas

  • Pediatrics, Perinatology, and Child Health
  • Surgery

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  • Cite this

    Hoshino, E., Hayashi, K., Suzuki, M., Obatake, M., Urayama, K. Y., Nakano, S., Taura, Y., Nio, M., & Takahashi, O. (2017). An iPhone application using a novel stool color detection algorithm for biliary atresia screening. Pediatric Surgery International, 33(10), 1115-1121. https://doi.org/10.1007/s00383-017-4146-8