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A novel mobile phone application for infant stool color recognition: An easy and effective tool to identify acholic
Roberta Angelico1,2, Daniela Liccardo3, Monica Paoletti1
1Division of Abdominal Transplantation and Hepatobiliopancreatic Surgery, Bambino Gesù Children's Hospital IRCCS, Rome, Italy.
Insights
A mobile app called PopòApp accurately identifies infant acholic stools, aiding early biliary atresia diagnosis. This tool shows high sensitivity and specificity, potentially improving patient outcomes.
Area of Science:
- Medical technology
- Pediatric gastroenterology
- Diagnostic tools
Background:
- Early diagnosis of biliary atresia is critical for improving long-term patient outcomes.
- Infant stool color cards are used for newborn screening to identify potential biliary atresia cases.
- A need exists for accessible and accurate tools to recognize acholic stools in infants.
Purpose of the Study:
- To develop and validate a mobile phone application, PopòApp, for identifying acholic stools in infants.
- To assess the accuracy of the PopòApp in classifying stool colors against a gold standard.
Main Methods:
- Developed an intuitive iOS and Android mobile application (PopòApp) utilizing a machine learning algorithm.
- Trained the algorithm on stool images from infants aged ≤6 months, referencing a seven-color infant stool color card.
- Validated the app's performance by comparing its classifications ('normal', 'acholic', 'uncertain') against independent expert physician diagnoses.
Main Results:
- The PopòApp achieved 100% sensitivity in recognizing acholic stools, with no false negatives.
- Specificity was 99.0%, and overall accuracy was 99.4%, demonstrating high reliability.
- The app showed a positive predictive value of 98.4% across various phone brands.
Conclusions:
- The PopòApp is a validated, accurate, and user-friendly tool for identifying acholic stools in a large cohort.
- This mobile application can serve as an effective strategy for early referral of infants with acholic stools.
- The PopòApp has the potential to significantly improve outcomes for children diagnosed with biliary atresia.
Objectives:
Early diagnosis of biliary atresia is essential to improve long-term outcomes. Newborn screening with an infant stool color card allows early recognition of biliary atresia patients. Our aim was to develop and validate a mobile phone application (PopòApp) able to identify acholic stools.
Methods:
An intuitive app was developed for iOS and Android smartphones. A learning machine process was used to generate an algorithm for stools color recognition based on the seven colors of the infant stool color card, which were considered as the gold standard. Consecutive images of stools were taken by the PopòApp, directly into the diapers of children aged ≤6 months. The PopòApp classified the photographs as "normal", "acholic" or "uncertain". To validate the PopòApp, four doctors independently classified all images, and only those for which all doctors agreed were included. The sensitivity, specificity, positive/negative predictive values, and accuracy of the PopòApp were evaluated.
Results:
Of 165 images collected, 160 were included in the study. All acholic stools were recognized by the PopòApp. The PopòApp sensitivity was 100% (95% CI:93.9%-100%) with no false negatives, regardless of the brand of phone. The specificity was 99.0% (95% CI:94.6%-99.9%). The accurancy of the PopòApp was 99.4% (95% CI:96.6%-99.9%), with a positive predictive value of 98.4% (95% CI:89.8%-99.8%).
Conclusion:
The current study proved, in a large cohort, that the PopòApp is an accurate and easy tool for recognition of acholic stools. The mobile App may represent an effective strategy for the early referral of children with acholic stools, and potentially could improve the outcomes of biliary atresia.
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