Mark Brommeyer, Maxine Whittaker, Zhanming Liang
Health Service Managers' Digital Competencies: A Conceptual Framework
Studies in health technology and informatics
identify infants abnormal suckling behavior simple nonnutritive suckling devices well known breastfeeding beneficial health mothers infants breastfeeding ceases 75 percent motherchild dyads 6 months current standard care lacks objective measurements screen infant suckling abnormalities within first days life critical time establish milk supply successful breastfeeding practices nonnutritive suckling vacuum measurement system previously developed authors used gather data 91 healthy fullterm infants thirty days old nonnutritive suckling recorded duration sixty seconds establish normative data mean suck vacuum maximum suck vacuum suckling frequency burst duration sucks per burst vacuum signal shape apply computational methods mahalanobis distance knn detect anomalies data identify infants abnormal suckling finally provide case studies healthy newborn infants infants diagnosed ankyloglossia series case evaluations demonstrate ability detect abnormal suckling behavior using statistical analysis machine learning evaluate cases ankyloglossia determine oral dysfunction surgical interventions affect nonnutritive suckling measurements statistical analysis mahalanobis distance machine learning k nearest neighbor knn viable approaches rapidly interpret infant suckling measurements particularly practices using digital suck assessment gloved finger provide objective early stage screening method identify abnormal infant suckling vacuum approach identifying risk breastfeeding complications crucial complement complex emerging clinical evaluation technology analyzing nonnutritive suckling using computational methods demonstrate ability detect abnormal normal behavior infant suckling inform breastfeeding intervention pathways clinicclinical translational impact statement work serves shed light lack consensus determining appropriate intervention pathways infant oral dysfunction demonstrate using statistical analysis machine learning normal abnormal infant suckling identified used determining surgical intervention necessary solution resolve infant feeding difficulties