AI Medical Compendium Topic:
Child

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Deep Learning Models for Abdominal CT Organ Segmentation in Children: Development and Validation in Internal and Heterogeneous Public Datasets.

AJR. American journal of roentgenology
Deep learning abdominal organ segmentation algorithms have shown excellent results in adults; validation in children is sparse. The purpose of this article is to develop and validate deep learning models for liver, spleen, and pancreas segmentation...

Machine Learning-Based Approach to Predict Last-Minute Cancellation of Pediatric Day Surgeries.

Computers, informatics, nursing : CIN
The last-minute cancellation of surgeries profoundly affects patients and their families. This research aimed to forecast these cancellations using EMR data and meteorological conditions at the time of the appointment, using a machine learning approa...

A machine learning model for the early diagnosis of bloodstream infection in patients admitted to the pediatric intensive care unit.

PloS one
Bloodstream infection (BSI) is associated with increased morbidity and mortality in the pediatric intensive care unit (PICU) and high healthcare costs. Early detection and appropriate treatment of BSI may improve patient's outcome. Data on machine-le...

Identifying ADHD-Related Abnormal Functional Connectivity with a Graph Convolutional Neural Network.

Neural plasticity
Attention deficit hyperactivity disorder (ADHD) is a common neurodevelopmental disorder that is characterized by inattention, hyperactivity, and impulsivity. The neural mechanisms underlying ADHD remain inadequately understood, and current approaches...

Expert-level sleep staging using an electrocardiography-only feed-forward neural network.

Computers in biology and medicine
Reliable classification of sleep stages is crucial in sleep medicine and neuroscience research for providing valuable insights, diagnoses, and understanding of brain states. The current gold standard method for sleep stage classification is polysomno...

Pediatric tympanostomy tube assessment via deep learning.

American journal of otolaryngology
PURPOSE: Tympanostomy tube (TT) placement is the most frequently performed ambulatory surgery in children under 15. After the procedure it is recommended that patients follow up regularly for "tube checks" until TT extrusion. Such visits incur direct...

Olecranon bone age assessment in puberty using a lateral elbow radiograph and a deep-learning model.

European radiology
OBJECTIVES: To improve pubertal bone age (BA) evaluation by developing a precise and practical elbow BA classification using the olecranon, and a deep-learning AI model.

Combining deep neural networks, a rule-based expert system and targeted manual coding for ICD-10 coding causes of death of French death certificates from 2018 to 2019.

International journal of medical informatics
OBJECTIVE: For ICD-10 coding causes of death in France in 2018 and 2019, predictions by deep neural networks (DNNs) are employed in addition to fully automatic batch coding by a rule-based expert system and to interactive coding by the coding team fo...

An individualized protein-based prognostic model to stratify pediatric patients with papillary thyroid carcinoma.

Nature communications
Pediatric papillary thyroid carcinomas (PPTCs) exhibit high inter-tumor heterogeneity and currently lack widely adopted recurrence risk stratification criteria. Hence, we propose a machine learning-based objective method to individually predict their...