AIMC Topic: Child

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Deep-learning segmentation of ultrasound images for automated calculation of the hydronephrosis area to renal parenchyma ratio.

Investigative and clinical urology
PURPOSE: We investigated the feasibility of measuring the hydronephrosis area to renal parenchyma (HARP) ratio from ultrasound images using a deep-learning network.

A pediatric wrist trauma X-ray dataset (GRAZPEDWRI-DX) for machine learning.

Scientific data
Digital radiography is widely available and the standard modality in trauma imaging, often enabling to diagnose pediatric wrist fractures. However, image interpretation requires time-consuming specialized training. Due to astonishing progress in comp...

Feasibility of Overground Gait Training Using a Joint-Torque-Assisting Wearable Exoskeletal Robot in Children with Static Brain Injury.

Sensors (Basel, Switzerland)
Pediatric gait disorders are often chronic and accompanied by various complications, which challenge rehabilitation efforts. Here, we retrospectively analyzed the feasibility of overground robot-assisted gait training (RAGT) using a joint-torque-assi...

Predicting risk of overweight or obesity in Chinese preschool-aged children using artificial intelligence techniques.

Endocrine
OBJECTIVES: We adopted the machine-learning algorithms and deep-learning sequential model to determine and optimize most important factors for overweight and obesity in Chinese preschool-aged children.

Enhancing robotic efficiency through the eyes of robotic surgeons: sub-analysis of the expertise in perception during robotic surgery (ExPeRtS) study.

Surgical endoscopy
BACKGROUND: Robotic technology affords surgeons many novel and useful features, but two stereotypes continue to prevail: robotic surgery is expensive and inefficient. To identify educational opportunities and improve operative efficiency, we analyzed...

Deep learning of birth-related infant clavicle fractures: a potential virtual consultant for fracture dating.

Pediatric radiology
BACKGROUND: In infant abuse investigations, dating of skeletal injuries from radiographs is desirable to reach a clear timeline of traumatic events. Prior studies have used infant birth-related clavicle fractures as a surrogate to develop a framework...

Parental Perceptions on Use of Artificial Intelligence in Pediatric Acute Care.

Academic pediatrics
BACKGROUND: Family engagement is critical in the implementation of artificial intelligence (AI)-based clinical decision support tools, which will play an increasing role in health care in the future. We sought to understand parental perceptions of co...

Sparking the Interest of Girls in Computer Science via Chemical Experimentation and Robotics: The Qui-Bot HO Case Study.

Sensors (Basel, Switzerland)
We report a new learning approach in science and technology through the Qui-Bot HO project: a multidisciplinary and interdisciplinary project developed with the main objective of inclusively increasing interest in computer science engineering among c...

A Deep Learning Approach to Estimate the Incidence of Infectious Disease Cases for Routinely Collected Ambulatory Records: The Example of Varicella-Zoster.

International journal of environmental research and public health
The burden of infectious diseases is crucial for both epidemiological surveillance and prompt public health response. A variety of data, including textual sources, can be fruitfully exploited. Dealing with unstructured data necessitates the use of me...

Automated segmentation of whole-body CT images for body composition analysis in pediatric patients using a deep neural network.

European radiology
OBJECTIVES: To develop an automatic segmentation algorithm using a deep neural network with transfer learning applicable to whole-body PET-CT images in children.