Application of Statistical Analysis and Machine Learning to Identify Infants’ Abnormal Suckling Behavior
Phuong Truong,
Erin Walsh,
Vanessa P. Scott
et al.
Abstract:Identify infants with abnormal suckling behavior from simple non-nutritive suckling devices. Background. While it is well known breastfeeding is beneficial to the health of both mothers and infants, breastfeeding ceases in 75 percent of motherchild dyads by 6 months. The current standard of care lacks objective measurements to screen infant suckling abnormalities within the first few days of life, a critical time to establish milk supply and successful breastfeeding practices. Materials and Methods: A non-nutr… Show more
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