AIMC Topic: Child

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Locomotor and robotic assistive gait training for children with cerebral palsy.

Developmental medicine and child neurology
AIM: To determine if robotic assisted gait training (RAGT) using surface muscle electrical stimulation and locomotor training enhances mobility outcomes when compared to locomotor training alone in children with cerebral palsy (CP).

Age verification using random forests on facial 3D landmarks.

Forensic science international
Three-dimensional facial images are becoming more and more widespread. As such images provide more information about facial morphology than 2D imagery, they show great promise for use in future forensic applications, including age estimation and veri...

Deep learning enabled prediction of 5-year survival in pediatric genitourinary rhabdomyosarcoma.

Surgical oncology
BACKGROUND: Genitourinary rhabdomyosarcoma (GU-RMS) is a rare, pediatric malignancy originating from embryonic mesenchyme. Current approaches to prognostication rely upon conventional statistical methods such as Cox proportional hazards (CPH) models ...

Identification of Latent Risk Clinical Attributes for Children Born Under IUGR Condition Using Machine Learning Techniques.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Intrauterine Growth Restriction (IUGR) is a condition in which a fetus does not grow to the expected weight during pregnancy. There are several well documented causes in the literature for this issue, such as maternal disord...

Computer-aided diagnosis of pectus excavatum using CT images and deep learning methods.

Scientific reports
Pectus excavatum (PE) is one of the most common chest wall defects. Accurate assessment of PE deformities is critical for effective surgical intervention. Index-based evaluations have become the standard for objectively estimating PE, however, these ...

A data driven methodology for social science research with left-behind children as a case study.

PloS one
For decades, traditional correlation analysis and regression models have been used in social science research. However, the development of machine learning algorithms makes it possible to apply machine learning techniques for social science research ...

Automatic eye localization for hospitalized infants and children using convolutional neural networks.

International journal of medical informatics
BACKGROUND: Reliable localization and tracking of the eye region in the pediatric hospital environment is a significant challenge for clinical decision support and patient monitoring applications. Existing work in eye localization achieves high perfo...

Perspectives of Child Life Specialists After Many Years of Working With a Humanoid Robot in a Pediatric Hospital: Narrative Design.

Journal of medical Internet research
BACKGROUND: Child life specialists (CLSs) play an important role in supporting patients and their families during their visits to a children's hospital. Although CLSs are equipped with considerable expertise to support families during some of the mos...

Learning Bayesian networks from demographic and health survey data.

Journal of biomedical informatics
Child mortality from preventable diseases such as pneumonia and diarrhoea in low and middle-income countries remains a serious global challenge. We combine knowledge with available Demographic and Health Survey (DHS) data from India, to construct Cau...