Manuck, TA et al. “Preterm neonatal morbidity and mortality by gestational age: a contemporary cohort.” Am. J. Obstet. Gynecol. 215103.e101–103.e114 (2016).
Harrison, W. & Goodman, D. Epidemiological trends in neonatal intensive care, 2007-2012. JAMA Pediatrics 169855–862 (2015).
Braun, D. et al., “Trends in Neonatal Intensive Care Unit Utilization in a Large Integrated Healthcare System.” JAMA Network Open 3e205239 (2020).
Jarjour, I. T. Neurodevelopmental outcome after extreme prematurity: a review of the literature. Pediatric Neurology 52143–152 (2015).
Raju, TN, Higgins, RD, Stark, AR, Leveno, KJ Optimizing care and outcomes for late preterm (near term) infants: summary of a workshop sponsored by the National Institute of Child Health and Human Development. Pediatrics 1181207–1214 (2006).
Gurka, M.J., LoCasale-Crouch, J. & Blackman, J.A. Long-term cognitive, achievement, socio-emotional, and behavioral development of healthy late preterm infants. Arch. Pediatrics. Medicine. 164525–532 (2010).
Subedi, D., DeBoer, MD & Scharf, RJ Developmental trajectories of children with extended NICU stays. Arch This Child 10229–34 (2017).
van Wassenaer-Leemhuis, AG et al. “Rethinking post-discharge preventive intervention programs for extremely preterm infants and their parents” Developmental Medicine and Pediatric Neurology 5867–73 (2016).
Santos, J., Pearce, S. E., Stroustrup, A. The impact of hospital environmental exposures on neurodevelopmental outcomes in preterm infants. Curr. Opin. Pediatr. 27254–260 (2015).
Synnes, A. & Hicks, M. Neurodevelopmental outcomes of preterm infants beyond school age. Clinical Perinatol 45393–408 (2018).
Williams, C.N., Kirby, A., and Piantino, J. “Build it and they will come: Initial experiences with a multidisciplinary pediatric neurocritical care follow-up clinic.” Children (Basel) Four83 (2017).
Vohr, B. et al. “Follow-up Care of High-Risk Infants” Pediatrics 1141377–1397 (2004).
McAdams, RM et al. “Predicting clinical outcomes in the neonatal intensive care unit using artificial intelligence and machine learning: a systematic review.” J. Perinatol. 421561–1575 (2022).
Mangold, C. et al. “Machine learning models for predicting neonatal mortality: a systematic review.” Neonatology 118394–405 (2021).
Hathaway, QA et al. Machine learning to stratify diabetes patients using novel cardiac biomarkers and integrated genomics. Cardiovascular. Diabetes. 1878 (2019).
Cheraghlou, S., Sadda, P., Agogo, G.O. & Girardi, M. Machine learning improved CART algorithm predicts prognosis in Merkel cell carcinoma. Australas. J. Dermatology 62323–330 (2021).
Sheikhtaheri, A., Zarkesh, M. R., Moradi, R., Kermani, F. Prediction of neonatal mortality in the NICU: development and validation of a machine learning model. BMC Med Inf. Decision. Mak. twenty one131 (2021).
Guedalia, J. et al. “Primary risk stratification of neonatal jaundice in term neonates using machine learning algorithms.” Early HAM development. 165105538 (2022).
Van Laere, D. et al. “Machine learning to support hemodynamic interventions in the neonatal intensive care unit.” Clinical Perinatol 47435–448 (2020).
Boyle, C.A. et al., “Trends in the Prevalence of Developmental Disabilities among U.S. Children, 1997-2008.” Pediatrics 1271034–1042 (2011).
Holmes, JF et al. “Validation of a Prediction Rule for Identifying Children with Intra-Abdominal Injuries Following Blunt Torso Trauma” Emergency medical care 54528–533 (2009).
Eisenbrown, K., Nimmer, M., Ellison, AM, Simpson, P. & Brousseau, DC Which febrile children with sickle cell disease require a chest x-ray? Academy of Emergency Medicine twenty three1248–1256 (2016).
Rigatti, S.J. Random forests. J.InsurMed 4731–39 (2017).
Zhang, Z., Zhao, Y., Canes, A., Steinberg, D., Lyashevska, O. Predictive analytics with gradient boosting in clinical medicine. Ann.Transl.Medical. 7152 (2019).
Lu, R. et al. Application of multivariate adaptive regression splines in investigating the influencing factors and predicting the prevalence of Hba1c improvement. Ann Pariat Medicine Ten1296–1303 (2021).
Brathwaite, R. et al., “Predicting Individual Risk of Poor Adherence to ART Treatment Among HIV-Infected Adolescents in Uganda: The Suubi+Adherence Study.” International Journal of AIDS twenty foure25756 (2021).
Glinianaia, SV et al. “Long-term survival of children born with congenital anomalies: a systematic review and meta-analysis of population-based studies.” PLoS Med. 17e1003356 (2020).
Awad, A., Bader-El-Den, M., McNicholas, J., Briggs, J. Predicting early in-hospital mortality in intensive care unit patients using an ensemble learning approach. International Journal of Medical Information 108185–195 (2017).
Ye, C. et al. “Real-time early warning system for monitoring the risk of mortality in hospitalized patients: a prospective study using electronic medical record data.” J. Med Internet Research twenty onee13719 (2019).
Ambalavanan, N. & Carlo, W. A. Comparison of prediction of very low birth weight neonatal mortality using regression analysis and neural networks. Early HAM development. 65123–137 (2001).
Ambalavanan, N. et al. “Predicting Mortality in Very Low Birth Weight Newborns” Pediatrics 1161367–1373 (2005).
Warren, MG et al. “Gastrostomy tube feeding in very low birth weight infants: incidence, associated complications, and long-term outcomes.” Pediatric Journal 21441–46.e45 (2019).
Lagatta, JM, et al., “The Actual and Potential Impact of a Home Nasogastric Tube Feeding Program for Infants Affected by Delayed Oral Intake Upon Discharge from the Neonatal Intensive Care Unit.” Pediatric Journal 23438–45.e32 (2021).
Patra, K. & Greene, M. M. Health care utilization after NICU discharge and neurodevelopmental outcomes in preterm infants during the first 2 years of life. Am. J. Perinatol. 35441–447 (2018).
Gaglioti, P. et al. “Fetal ventriculomegaly: results of 176 cases.” Ultrasound Obstetrics and Gynecology twenty five372–377 (2005).
Brosig, CL et al. “Preschool Neurodevelopmental Outcomes of Children with Congenital Heart Disease.” Pediatric Journal 18380–86.e81 (2017).
Patra, K. & Greene, M. M. The impact of feeding disorders in the NICU on neurodevelopmental outcomes at 8 and 20 months corrected age in extremely low gestational age infants. J. Perinatol. 391241–1248 (2019).
Giannì, ML et al. The impact of comorbidities on the development of oral feeding skills in preterm infants: a retrospective study. Scientific Representative Five16603 (2015).
Wolthuis-Stigter, MI et al. Associations between sucking behavior in preterm infants and neurodevelopmental outcomes at 2 years of age. Pediatric Journal 16626–30.e21 (2015).
