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

作者：Hoshino Eri^*; Hayashi Kuniyoshi; Suzuki Mitsuyoshi; Obatake Masayuki; Urayama Kevin Y; Nakano Satoshi; Taura Yasuyuki; Nio Masaki; Takahashi Osamu

来源：Pediatric Surgery International, 2017, 33(10): 1115-1121.

DOI：10.1007/s00383-017-4146-8

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

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.
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.
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.
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.

• 出版日期2017-10