AI Medical Compendium Topic:
Infant

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Statistical supervised meta-ensemble algorithm for medical record linkage.

Journal of biomedical informatics
Identifying unique patients across multiple care facilities or services is a major challenge in providing continuous care and undertaking health research. Identifying and linking patients without compromising privacy and security is an emerging issue...

Topological correction of infant white matter surfaces using anatomically constrained convolutional neural network.

NeuroImage
Reconstruction of accurate cortical surfaces without topological errors (i.e., handles and holes) from infant brain MR images is very important in early brain development studies. However, infant brain MR images typically suffer extremely low tissue ...

Precise diagnosis of intracranial hemorrhage and subtypes using a three-dimensional joint convolutional and recurrent neural network.

European radiology
OBJECTIVES: To evaluate the performance of a novel three-dimensional (3D) joint convolutional and recurrent neural network (CNN-RNN) for the detection of intracranial hemorrhage (ICH) and its five subtypes (cerebral parenchymal, intraventricular, sub...

Incorporated region detection and classification using deep convolutional networks for bone age assessment.

Artificial intelligence in medicine
Bone age assessment plays an important role in the endocrinology and genetic investigation of patients. In this paper, we proposed a deep learning-based approach for bone age assessment by integration of the Tanner-Whitehouse (TW3) methods and deep c...

Comparison of Deep Learning Approaches for Multi-Label Chest X-Ray Classification.

Scientific reports
The increased availability of labeled X-ray image archives (e.g. ChestX-ray14 dataset) has triggered a growing interest in deep learning techniques. To provide better insight into the different approaches, and their applications to chest X-ray classi...

Machine learning accurately classifies age of toddlers based on eye tracking.

Scientific reports
How people extract visual information from complex scenes provides important information about cognitive processes. Eye tracking studies that have used naturalistic, rather than highly controlled experimental stimuli, reveal that variability in looki...

Main factors influencing recovery in MERS Co-V patients using machine learning.

Journal of infection and public health
BACKGROUND: Middle East Respiratory Syndrome (MERS) is a major infectious disease which has affected the Middle Eastern countries, especially the Kingdom of Saudi Arabia (KSA) since 2012. The high mortality rate associated with this disease has been ...

Use of Machine Learning in the Analysis of Indoor ELF MF Exposure in Children.

International journal of environmental research and public health
Characterization of children exposure to extremely low frequency (ELF) magnetic fields is an important issue because of the possible correlation of leukemia onset with ELF exposure. Cluster analysis-a Machine Learning approach-was applied on personal...

Deep learning for identifying environmental risk factors of acute respiratory diseases in Beijing, China: implications for population with different age and gender.

International journal of environmental health research
This study focuses on identifying environmental health risk factors related to acute respiratory diseases using deep learning method. Based on respiratory disease data, air pollution data and meteorological environmental data, cross-domain risk facto...

Robot-assisted laparoscopic midureteral stricture repair and percutaneous stent placement in an infant.

Journal of pediatric urology
Mid-ureteral strictures in infants are a rare cause of hydronephrosis. In this surgical technique video we demonstrate a repair of a mid-ureteral stricture using a robot- assisted laparoscopic approach to mobilize and excise the stricture using the a...