AIMC Topic: Infant, Newborn

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Machine-learning analysis outperforms conventional statistical models and CT classification systems in predicting 6-month outcomes in pediatric patients sustaining traumatic brain injury.

Neurosurgical focus Nov 1, 2018
OBJECTIVEModern surgical planning and prognostication requires the most accurate outcomes data to practice evidence-based medicine. For clinicians treating children following traumatic brain injury (TBI) these data are severely lacking. The first aim...
Humans Machine Learning Electronic Health Records Female Infant, Newborn Child Treatment Outcome Brain Injuries, Traumatic Models, Statistical International Classification of Diseases Male Infant Adolescent Time Factors Child, Preschool
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MABAL: a Novel Deep-Learning Architecture for Machine-Assisted Bone Age Labeling.

Journal of digital imaging Aug 1, 2018
Bone age assessment (BAA) is a commonly performed diagnostic study in pediatric radiology to assess skeletal maturity. The most commonly utilized method for assessment of BAA is the Greulich and Pyle method (Pediatr Radiol 46.9:1269-1274, 2016; Arch ...
Child, Preschool Female Child Infant Infant, Newborn Humans Pediatrics Sensitivity and Specificity Diagnosis, Computer-Assisted Age Determination by Skeleton Neural Networks, Computer Male Deep Learning Machine Learning Adolescent Databases, Factual Cohort Studies Retrospective Studies
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Investigating the Impact of CNN Depth on Neonatal Seizure Detection Performance.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Jul 1, 2018
This study presents a novel, deep, fully convolutional architecture which is optimized for the task of EEG-based neonatal seizure detection. Architectures of different depths were designed and tested; varying network depth impacts convolutional recep...
Support Vector Machine Electroencephalography Seizures Humans Neural Networks, Computer Infant, Newborn Image Processing, Computer-Assisted
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Automated Assessment of Bone Age Using Deep Learning and Gaussian Process Regression.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Jul 1, 2018
Bone age is an essential measure of skeletal maturity in children with growth disorders. It is typically assessed by a trained physician using radiographs of the hand and a reference model. However, it has been described that the reference models lea...
Hand Bones Image Interpretation, Computer-Assisted Observer Variation Normal Distribution Age Determination by Skeleton Female Infant, Newborn Young Adult Infant Deep Learning Adolescent Child, Preschool Child Radiography Humans Retrospective Studies
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Automated Diagnosis of Plus Disease in Retinopathy of Prematurity Using Deep Convolutional Neural Networks.

JAMA ophthalmology Jul 1, 2018
IMPORTANCE: Retinopathy of prematurity (ROP) is a leading cause of childhood blindness worldwide. The decision to treat is primarily based on the presence of plus disease, defined as dilation and tortuosity of retinal vessels. However, clinical diagn...
Humans Neural Networks, Computer Algorithms Female Infant Deep Learning ROC Curve Image Interpretation, Computer-Assisted Infant, Premature Infant, Newborn Reproducibility of Results Sensitivity and Specificity Male Gestational Age Retinopathy of Prematurity Photography Retinal Vessels
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Use of Fetal Magnetic Resonance Image Analysis and Machine Learning to Predict the Need for Postnatal Cerebrospinal Fluid Diversion in Fetal Ventriculomegaly.

JAMA pediatrics Feb 1, 2018
IMPORTANCE: Which children with fetal ventriculomegaly, or enlargement of the cerebral ventricles in utero, will develop hydrocephalus requiring treatment after birth is unclear.
Predictive Value of Tests Hydrocephalus Image Interpretation, Computer-Assisted Prenatal Diagnosis Pregnancy Female Infant, Newborn Case-Control Studies Magnetic Resonance Imaging Humans Machine Learning Retrospective Studies
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Using Clinical Notes and Natural Language Processing for Automated HIV Risk Assessment.

Journal of acquired immune deficiency syndromes (1999) Feb 1, 2018
OBJECTIVE: Universal HIV screening programs are costly, labor intensive, and often fail to identify high-risk individuals. Automated risk assessment methods that leverage longitudinal electronic health records (EHRs) could catalyze targeted screening...
Humans Algorithms Decision Support Techniques Electronic Health Records Infant Adolescent Female HIV Infections Young Adult Cohort Studies Child Infant, Newborn Adult Child, Preschool Mass Screening Male Risk Factors Natural Language Processing Middle Aged Aged Automation Risk Assessment Aged, 80 and over New York City
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Levels and effectiveness of oral retinol supplementation in VLBW preterm infants.

International journal of immunopathology and pharmacology Jan 1, 2018
Retinol palmitate oral administration is convenient, but it is difficult to assess/monitor its nutritional status in preterm infants and literature is controversial about the administration route and the effectiveness of vitamin A supplementation. We...
Infant, Low Birth Weight Dietary Supplements Humans Administration, Oral Female Vitamin A Infant, Newborn Nutritional Status Male Infant, Premature
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Postoperative neonatal mortality prediction using superlearning.

The Journal of surgical research Jan 1, 2018
BACKGROUND: The variable risks associated with neonatal surgery present a challenge to accurate mortality prediction. We aimed to apply superlearning, an ensemble machine learning method, to the prediction of 30-day neonatal postoperative mortality.
Humans Models, Theoretical Machine Learning Infant Mortality Female Algorithms Surgical Procedures, Operative Infant, Newborn Infant, Premature Male Infant United States
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Integrative Analysis of Proteomics Data to Obtain Clinically Relevant Markers.

Methods in molecular biology (Clifton, N.J.) Jan 1, 2018
The analysis of proteomics data can be significantly challenging. Beyond the technical challenges of accurately identifying and quantifying peptides, identifying the most biologically coherent set of biomarkers can be a particularly daunting step. In...
Sudden Infant Death Humans Principal Component Analysis Software Kidney Transplantation Graft Rejection Proteomics Biomarkers Workflow Proteome Knowledge Bases Infant, Newborn Signal Transduction Proteinuria Proteins
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