AI Medical Compendium Topic:
Child

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Social robotics as an adjuvant during the hospitalization process in pediatric oncology patients.

Journal of psychosocial oncology
OBJECTIVE: To describe the experience of implementing social robotics as an adjuvant during the hospitalization process in pediatric oncology patients.

Purely robotic ileocystoplasty in children: why not? First case in Spain.

Cirugia pediatrica : organo oficial de la Sociedad Espanola de Cirugia Pediatrica
INTRODUCTION: We present the first case of pediatric ileocystoplasty using a purely robotic approach in Spain.

Machine learning prediction model of major adverse outcomes after pediatric congenital heart surgery: a retrospective cohort study.

International journal of surgery (London, England)
BACKGROUND: Major adverse postoperative outcomes (APOs) can greatly affect mortality, hospital stay, care management and planning, and quality of life. This study aimed to evaluate the performance of five machine learning (ML) algorithms for predicti...

Identifying low acuity Emergency Department visits with a machine learning approach: The low acuity visit algorithms (LAVA).

Health services research
OBJECTIVE: To improve the performance of International Classification of Disease (ICD) code rule-based algorithms for identifying low acuity Emergency Department (ED) visits by using machine learning methods and additional covariates.

Explainable prediction of problematic smartphone use among South Korea's children and adolescents using a Machine learning approach.

International journal of medical informatics
BACKGROUND: Korea is known for its technological prowess, has the highest smartphone ownership rate in the world at 95%, and the smallest gap in smartphone ownership between generations. Since the onset of the COVID-19 pandemic, problematic smartphon...

Exploratory analysis using machine learning algorithms to predict pinch strength by anthropometric and socio-demographic features.

International journal of occupational safety and ergonomics : JOSE
. This study examines the role of different machine learning (ML) algorithms to determine which socio-demographic factors and hand-forearm anthropometric dimensions can be used to accurately predict hand function. . The cross-sectional study was cond...

Supervised representation learning based on various levels of pediatric radiographic views for transfer learning.

Scientific reports
Transfer learning plays a pivotal role in addressing the paucity of data, expediting training processes, and enhancing model performance. Nonetheless, the prevailing practice of transfer learning predominantly relies on pre-trained models designed fo...

Deep-Learning for Rapid Estimation of the Out-of-Field Dose in External Beam Photon Radiation Therapy - A Proof of Concept.

International journal of radiation oncology, biology, physics
PURPOSE: The dose deposited outside of the treatment field during external photon beam radiation therapy treatment, also known as out-of-field dose, is the subject of extensive study as it may be associated with a higher risk of developing a second c...

Correlative Assessment of Machine Learning-Based Cobb Angle Measurements and Human-Based Measurements in Adolescent Idiopathic and Congenital Scoliosis.

Canadian Association of Radiologists journal = Journal l'Association canadienne des radiologistes
Scoliosis is a complex spine deformity with direct functional and cosmetic impacts on the individual. The reference standard for assessing scoliosis severity is the Cobb angle which is measured on radiographs by human specialists, carrying interobse...