AIMC Topic: Child, Preschool

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Automated Lateral Ventricular and Cranial Vault Volume Measurements in 13,851 Patients Using Deep Learning Algorithms.

World neurosurgery
BACKGROUND: No large dataset-derived standard has been established for normal or pathologic human cerebral ventricular and cranial vault volumes. Automated volumetric measurements could be used to assist in diagnosis and follow-up of hydrocephalus or...

The Co-Pilot Project: An International Neurosurgical Collaboration in Ukraine.

World neurosurgery
OBJECTIVE: We aim to provide a thorough description of the efforts and outcomes of the Co-Pilot Project in Ukraine, which facilitates neurosurgical collaboration between American and Ukrainian physicians.

Deep Learning for Classification of Pediatric Otitis Media.

The Laryngoscope
OBJECTIVES/HYPOTHESIS: To create a new strategy for monitoring pediatric otitis media (OM), we developed a brief, reliable, and objective method for automated classification using convolutional neural networks (CNNs) with images from otoscope.

Sparse deep dictionary learning identifies differences of time-varying functional connectivity in brain neuro-developmental study.

Neural networks : the official journal of the International Neural Network Society
Recently, the focus of functional connectivity analysis of human brain has shifted from merely revealing the inter-regional functional correlation over the entire scan duration to capturing the time-varying information of brain networks and character...

Predicting the Development of Surgery-Related Pressure Injury Using a Machine Learning Algorithm Model.

The journal of nursing research : JNR
BACKGROUND: Surgery-related pressure injury (SRPI) is a serious problem in patients who undergo cardiovascular surgery. Identifying patients at a high risk of SRPI is important for clinicians to recognize and prevent it expeditiously. Machine learnin...

Reducing scan time of paediatric Tc-DMSA SPECT via deep learning.

Clinical radiology
AIM: To investigate the feasibility of reducing the scan time of paediatric technetium 99m (Tc) dimercaptosuccinic acid (DMSA) single-photon-emission computed tomographic (SPECT) using a deep learning (DL) method.

Machine Learning for Child and Adolescent Health: A Systematic Review.

Pediatrics
CONTEXT: In the last few decades, data acquisition and processing has seen tremendous amount of growth, thus sparking interest in machine learning (ML) within the health care system.

Detection of eye contact with deep neural networks is as accurate as human experts.

Nature communications
Eye contact is among the most primary means of social communication used by humans. Quantification of eye contact is valuable as a part of the analysis of social roles and communication skills, and for clinical screening. Estimating a subject's looki...

Automatic recognition of murmurs of ventricular septal defect using convolutional recurrent neural networks with temporal attentive pooling.

Scientific reports
Recognizing specific heart sound patterns is important for the diagnosis of structural heart diseases. However, the correct recognition of heart murmur depends largely on clinical experience. Accurately identifying abnormal heart sound patterns is ch...

Automatic seizure detection based on imaged-EEG signals through fully convolutional networks.

Scientific reports
Seizure detection is a routine process in epilepsy units requiring manual intervention of well-trained specialists. This process could be extensive, inefficient and time-consuming, especially for long term recordings. We proposed an automatic method ...