AIMC Topic: Infant, Newborn

Clear Filters Showing 81 to 90 of 743 articles

Longitudinal twin growth discordance patterns and adverse perinatal outcomes.

American journal of obstetrics and gynecology Jan 7, 2025
BACKGROUND: Growth discordance in twin pregnancies is associated with increased perinatal morbidity and mortality, yet the patterns of discordance progression and the utility of Doppler assessments remain underinvestigated.
Retrospective Studies Pregnancy Female Infant, Newborn Adult Humans Machine Learning Middle Cerebral Artery Fetal Growth Retardation Umbilical Arteries Perinatal Mortality Pregnancy, Twin Ultrasonography, Prenatal Pregnancy Outcome Longitudinal Studies Ultrasonography, Doppler Gestational Age
View on PubMed DOI

Fine-Grained Fidgety Movement Classification Using Active Learning.

IEEE journal of biomedical and health informatics Jan 7, 2025
Typically developing infants, between the corrected age of 9-20 weeks, produce fidgety movements. These movements can be identified with the General Movement Assessment, but their identification requires trained professionals to conduct the assessmen...
Problem-Based Learning Humans Male Movement Infant Algorithms Image Processing, Computer-Assisted Female Supervised Machine Learning Infant, Newborn Video Recording
View on PubMed DOI

Decoding of pain during heel lancing in human neonates with EEG signal and machine learning approach.

Scientific reports Dec 28, 2024
Currently, pain assessment using electroencephalogram signals and machine learning methods in clinical studies is of great importance, especially for those who cannot express their pain. Since newborns are among the high-risk group and always experie...
Heel Humans Male Machine Learning Support Vector Machine Pain Measurement Female Electroencephalography Infant, Newborn Pain
View on PubMed DOI

Trajectory of breastfeeding among Chinese women and risk prediction models based on machine learning: a cohort study.

BMC pregnancy and childbirth Dec 24, 2024
BACKGROUND: Breastfeeding is the optimal source of nutrition for infants and young children, essential for their healthy growth and development. However, a gap in cohort studies tracking breastfeeding up to six months postpartum may lead caregivers t...
Cohort Studies East Asian People Breast Feeding Postpartum Period Risk Assessment Infant China Humans Pregnancy Surveys and Questionnaires Machine Learning Female Prospective Studies Infant, Newborn Young Adult Adult
View on PubMed DOI

Predicting preterm birth using electronic medical records from multiple prenatal visits.

BMC pregnancy and childbirth Dec 21, 2024
This study aimed to predict preterm birth in nulliparous women using machine learning and easily accessible variables from prenatal visits. Elastic net regularized logistic regression models were developed and evaluated using 5-fold cross-validation ...
Predictive Value of Tests Area Under Curve Gestational Age Cervical Length Measurement Ultrasonography, Prenatal Humans Prenatal Care Risk Assessment Infant, Newborn Logistic Models Machine Learning Premature Birth Electronic Health Records Young Adult Pregnancy Adult Female Sensitivity and Specificity
View on PubMed DOI

Evaluation of Pregnancy Risks in Women with Subchorionic Hematoma Using Machine Learning Models.

Medical science monitor : international medical journal of experimental and clinical research Dec 21, 2024
BACKGROUND Subchorionic hematoma (SCH) can lead to blood accumulation and potentially affect pregnancy outcomes. Despite being a relatively common finding in early pregnancy, the effects of SCH on pregnancy outcomes such as miscarriage, stillbirth, a...
Machine Learning Pregnancy Female Infant, Newborn Gestational Age Premature Birth Stillbirth Risk Factors Humans Adult Chorion Birth Weight Pregnancy Outcome Logistic Models Abortion, Spontaneous Hematoma Pregnancy Complications
View on PubMed DOI

Using artificial intelligence to predict post-operative outcomes in congenital heart surgeries: a systematic review.

BMC cardiovascular disorders Dec 20, 2024
INTRODUCTION: Congenital heart disease (CHD) represents the most common group of congenital anomalies, constitutes a significant contributor to the burden of non-communicable diseases, highlighting the critical need for improved risk assessment tools...
Child Infant Treatment Outcome Decision Support Techniques Predictive Value of Tests Adolescent Female Cardiac Surgical Procedures Time Factors Infant, Newborn Heart Defects, Congenital Humans Child, Preschool Risk Factors Artificial Intelligence Young Adult Adult Male Risk Assessment Postoperative Complications
View on PubMed DOI

Development of a machine learning model for prediction of intraventricular hemorrhage in premature neonates.

Child's nervous system : ChNS : official journal of the International Society for Pediatric Neurosurgery Dec 16, 2024
PURPOSE: Intraventricular hemorrhage (IVH) is a common and severe complication in premature neonates, leading to long-term neurological impairments. Early prediction and identification of risk factors for IVH in premature neonates are crucial for imp...
Infant, Premature Gestational Age Infant, Premature, Diseases Cerebral Intraventricular Hemorrhage Humans Machine Learning Algorithms Retrospective Studies Female Infant, Newborn Risk Factors Male Cerebral Hemorrhage
View on PubMed DOI

Automatic Segmentation of Sylvian Fissure in Brain Ultrasound Images of Pre-Term Infants Using Deep Learning Models.

Ultrasound in medicine & biology Dec 15, 2024
OBJECTIVE: Segmentation of brain sulci in pre-term infants is crucial for monitoring their development. While magnetic resonance imaging has been used for this purpose, cranial ultrasound (cUS) is the primary imaging technique used in clinical practi...
Humans Brain Female Infant, Newborn Male Deep Learning Ultrasonography Infant, Premature
View on PubMed DOI

Firearm Injury Risk Prediction Among Children Transported by 9-1-1 Emergency Medical Services: A Machine Learning Analysis.

Pediatric emergency care Dec 12, 2024
OBJECTIVE: Among children transported by ambulance across the United States, we used machine learning models to develop a risk prediction tool for firearm injury using basic demographic information and home ZIP code matched to publicly available data...
Machine Learning Female Infant, Newborn Risk Factors Male Humans Child United States Emergency Medical Services Ambulances Wounds, Gunshot Risk Assessment Infant Adolescent Child, Preschool
View on PubMed DOI
Popular Topics
Recent Journals