Machine learning and stool consistency: a tale of scales
This webinar highlights the clinical relevance of stool patterns in pediatric health and introduces an AI-powered image recognition algorithm developed to assess stool consistency and color. Presented by Dr. Thomas Ludwig, Pediatric Gastroenterologist, the session explores how digital tools such as the stool tracker can distinguish differences in stool patterns based on diet type (formula vs. breast milk), age, and other variables.
The algorithm provides insights valuable in both randomized controlled trials and real-world evidence settings, offering detailed, data-driven support for healthcare professionals during pediatric consultations.
Continue watching:
Part 1: Health care professionals and AI: Adapt or be left behind
Part 2: An image recognition algorithm that estimates length/height and weight of infant
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Machine learning and stool consistency: a tale of scales
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