AIMC Topic: Child

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Developing a machine learning model to detect diagnostic uncertainty in clinical documentation.

Journal of hospital medicine
BACKGROUND AND OBJECTIVE: Diagnostic uncertainty, when unrecognized or poorly communicated, can result in diagnostic error. However, diagnostic uncertainty is challenging to study due to a lack of validated identification methods. This study aims to ...

A real-time automated bone age assessment system based on the RUS-CHN method.

Frontiers in endocrinology
BACKGROUND: Bone age is the age of skeletal development and is a direct indicator of physical growth and development in children. Most bone age assessment (BAA) systems use direct regression with the entire hand bone map or first segmenting the regio...

The effect of soft palate reconstruction with the da Vinci robot on middle ear function in children: an observational study.

International journal of oral and maxillofacial surgery
Cleft palate is associated with a high prevalence of middle ear dysfunction, even after palatal repair. The aim of this study was to evaluate the effects of robot-enhanced soft palate closure on middle ear functioning. This retrospective study compar...

A Patch-Based Deep Learning Approach for Detecting Rib Fractures on Frontal Radiographs in Young Children.

Journal of digital imaging
Chest radiography is the modality of choice for the identification of rib fractures in young children and there is value for the development of computer-aided rib fracture detection in this age group. However, the automated identification of rib frac...

Better Data from AI Users: A Field Experiment on the Impacts of Robot Self-Disclosure on the Utterance of Child Users in Home Environment.

Sensors (Basel, Switzerland)
Data are one of the important factors in artificial intelligence (AI). Moreover, in order for AI to understand the user and go beyond the role of a simple machine, the data contained in the user's self-disclosure is required. In this study, two types...

Deep convolutional neural network-the evaluation of cervical vertebrae maturation.

Oral radiology
OBJECTIVES: This study aimed to automatically determine the cervical vertebral maturation (CVM) processes on lateral cephalometric radiograph images using a proposed deep learning-based convolutional neural network (CNN) model and to test the success...

Successful all robotic-assisted excision of highly malignant mediastinal neuroblastoma in a toddler: A case report.

Asian journal of endoscopic surgery
An otherwise well 28-month-old girl presented with fever/left thigh pain. Computed tomography identified a 7 cm right posterior mediastinal tumor extending to the paravertebral and intercostal spaces with multiple bone and bone marrow metastases on b...

Deep Learning-Based Computed Tomography Image Standardization to Improve Generalizability of Deep Learning-Based Hepatic Segmentation.

Korean journal of radiology
OBJECTIVE: We aimed to investigate whether image standardization using deep learning-based computed tomography (CT) image conversion would improve the performance of deep learning-based automated hepatic segmentation across various reconstruction met...

AppraisalCloudPCT: A Computational Model of Emotions for Socially Interactive Robots for Autistic Rehabilitation.

Computational intelligence and neuroscience
Computational models of emotions can not only improve the effectiveness and efficiency of human-robot interaction but also coordinate a robot to adapt to its environment better. When designing computational models of emotions for socially interactive...

Comparison of diagnostic performance of a deep learning algorithm, emergency physicians, junior radiologists and senior radiologists in the detection of appendicular fractures in children.

Pediatric radiology
BACKGROUND: Advances have been made in the use of artificial intelligence (AI) in the field of diagnostic imaging, particularly in the detection of fractures on conventional radiographs. Studies looking at the detection of fractures in the pediatric ...