AIMC Topic: Infant

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Eliminating the need for manual segmentation to determine size and volume from MRI. A proof of concept on segmenting the lateral ventricles.

PloS one
Manual segmentation, which is tedious, time-consuming, and operator-dependent, is currently used as the gold standard to validate automatic and semiautomatic methods that quantify geometries from 2D and 3D MR images. This study examines the accuracy ...

Deep learning-guided postoperative pain assessment in children.

Pain
Current automated pain assessment methods only focus on infants or youth. They are less practical because the children who suffer from postoperative pain in clinical scenarios are in a wider range of ages. In this article, we present a large-scale Cl...

Diagnostic accuracy of a deep learning model using YOLOv5 for detecting developmental dysplasia of the hip on radiography images.

Scientific reports
Developmental dysplasia of the hip (DDH) is a cluster of hip development disorders and one of the most common hip diseases in infants. Hip radiography is a convenient diagnostic tool for DDH, but its diagnostic accuracy is dependent on the interprete...

Development and international validation of custom-engineered and code-free deep-learning models for detection of plus disease in retinopathy of prematurity: a retrospective study.

The Lancet. Digital health
BACKGROUND: Retinopathy of prematurity (ROP), a leading cause of childhood blindness, is diagnosed through interval screening by paediatric ophthalmologists. However, improved survival of premature neonates coupled with a scarcity of available expert...

Revisiting the video deficit in technology-saturated environments: Successful imitation from people, screens, and social robots.

Journal of experimental child psychology
The "video deficit" is a well-documented effect whereby children learn less well about information delivered via a screen than the same information delivered in person. Research suggests that increasing social contingency may ameliorate this video de...

Comparison of End-to-End Neural Network Architectures and Data Augmentation Methods for Automatic Infant Motility Assessment Using Wearable Sensors.

Sensors (Basel, Switzerland)
Infant motility assessment using intelligent wearables is a promising new approach for assessment of infant neurophysiological development, and where efficient signal analysis plays a central role. This study investigates the use of different end-to-...

And then there was one … incision. First single-port pediatric robotic case series.

Journal of pediatric urology
BACKGROUND: In the past two decades, technology has advanced to augment an already minimally-invasive approach in laparoscopic surgery. Robotic-assisted laparoscopic platforms have now evolved to its 4th-generation product: a single-port system, firs...

Of children and social robots.

The Behavioral and brain sciences
In the target article, Clark and Fischer argue that little is known about children's perceptions of social robots. By reviewing the existing literature we demonstrate that infants and young children interact with robots in the same ways they do with ...

Robot-Assisted Prostatic Utricle Reconstruction Using the Carrel Patch Principle to Preserve Fertility.

Urology
BACKGROUND: Prostatic utricle (PU) with normal external genitalia is an uncommon congenital anomaly. About 14% develop epididymitis. This rare presentation should warn involvement of the ejaculatory ducts. Minimally invasive robot-assisted utricle re...