AIMC Topic: Infant, Newborn

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[Development and evaluation of a machine learning prediction model for large for gestational age].

Zhonghua liu xing bing xue za zhi = Zhonghua liuxingbingxue zazhi
To develop and validate a useful predictive model for large gestational age (LGA) in pregnancy using a machine learning (ML) algorithm and compare its performance with the traditional logistic regression model. Data were obtained from the National ...

Single-Examination Risk Prediction of Severe Retinopathy of Prematurity.

Pediatrics
BACKGROUND AND OBJECTIVES: Retinopathy of prematurity (ROP) is a leading cause of childhood blindness. Screening and treatment reduces this risk, but requires multiple examinations of infants, most of whom will not develop severe disease. Previous wo...

phyLoSTM: a novel deep learning model on disease prediction from longitudinal microbiome data.

Bioinformatics (Oxford, England)
MOTIVATION: Research shows that human microbiome is highly dynamic on longitudinal timescales, changing dynamically with diet, or due to medical interventions. In this article, we propose a novel deep learning framework 'phyLoSTM', using a combinatio...

Asymmetric Three-dimensional Convolutions For Preterm Infants' Pose Estimation.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Computer-assisted tools for preterm infants' movement monitoring in neonatal intensive care unit (NICU) could support clinicians in highlighting preterm-birth complications. With such a view, in this work we propose a deep-learning framework for pret...

Towards Deeper Neural Networks for Neonatal Seizure Detection.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Machine learning and more recently deep learning have become valuable tools in clinical decision making for neonatal seizure detection. This work proposes a deep neural network architecture which is capable of extracting information from long segment...

Towards real-time diagnosis for pediatric sepsis using graph neural network and ensemble methods.

European review for medical and pharmacological sciences
OBJECTIVE: The rapid onset of pediatric sepsis and the short optimal time for resuscitation pose a severe threat to children's health in the ICU. Timely diagnosis and intervention are essential to curing sepsis, but there is a lack of research on the...

Prediction of Adult Height by Machine Learning Technique.

The Journal of clinical endocrinology and metabolism
CONTEXT: Prediction of AH is frequently undertaken in the clinical setting. The commonly used methods are based on the assessment of skeletal maturation. Predictive algorithms generated by machine learning, which can already automatically drive cars ...

Mining tasks and task characteristics from electronic health record audit logs with unsupervised machine learning.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: The characteristics of clinician activities while interacting with electronic health record (EHR) systems can influence the time spent in EHRs and workload. This study aims to characterize EHR activities as tasks and define novel, data-dri...