Pediatrics

Latest AI and machine learning research in pediatrics for healthcare professionals.

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Predicting Agitation-Sedation Levels in Intensive Care Unit Patients: Development of an Ensemble Model.

BACKGROUND: Agitation and sedation management is critical in intensive care as it affects patient sa...

The predictive role of sedentary behavior and physical activity on adolescent depressive symptoms: A machine learning approach.

OBJECTIVE: This study aims to investigate the predictive value of sedentary behavior and physical ac...

Continuous non-contact monitoring of neonatal activity.

PURPOSE: Neonatal activity is an important physiological parameter in the neonatal intensive care un...

Using machine learning to predict poor adherence to antiretroviral therapy among adolescents with HIV in low resource settings.

OBJECTIVES: Achieving optimal adherence to antiretroviral therapy (ART) and viral suppression is sti...

Artificial intelligence in managing retinal disease-current concepts and relevant aspects for health care providers.

Given how the diagnosis and management of many ocular and, most specifically, retinal diseases heavi...

Development of the autonomous lab system to support biotechnology research.

In this study, we developed the autonomous lab (ANL), which is a system based on robotics and artifi...

Machine Learning-Based Prediction of Substance Use in Adolescents in Three Independent Worldwide Cohorts: Algorithm Development and Validation Study.

BACKGROUND: To address gaps in global understanding of cultural and social variations, this study us...

Hypothesis: Net benefit as an objective function during development of machine learning algorithms for medical applications.

Net benefit is the most widely used metric for evaluating the clinical utility of medical prediction...

Feasibility study of texture-based machine learning approach for early detection of neonatal jaundice.

Untreated neonatal jaundice can have severe consequences. Effective screening for neonatal jaundice ...

Enhanced recognition and counting of high-coverage Amorphophallus konjac by integrating UAV RGB imagery and deep learning.

Accurate counting of Amorphophallus konjac (Konjac) plants can offer valuable insights for agricultu...

Impact of deep learning on pediatric elbow fracture detection: a systematic review and meta-analysis.

OBJECTIVES: Pediatric elbow fractures are a common injury among children. Recent advancements in art...

SegFormer3D: Improving the Robustness of Deep Learning Model-Based Image Segmentation in Ultrasound Volumes of the Pediatric Hip.

Developmental dysplasia of the hip (DDH) is a painful orthopedic malformation diagnosed at birth in ...

Artificial Intelligence non-invasive methods for neonatal jaundice detection: A review.

Neonatal jaundice is a common and potentially fatal health condition in neonates, especially in low ...

Predicting PTSD development with early post-trauma assessments: a proof-of-concept for a concise tree-based classification method.

Approximately 70% of individuals globally experience at least one traumatic event in their lifetime...

AI for glaucoma, Are we reporting well? a systematic literature review of DECIDE-AI checklist adherence.

BACKGROUND/OBJECTIVES: This systematic literature review examines the quality of early clinical eval...

Machine learning insights into calcium phosphate nucleation and aggregation.

In this study, we utilized machine learning interatomic potentials (MLIPs) to investigate the nuclea...

AI-facilitated home monitoring for cystic fibrosis exacerbations across pediatric and adult populations.

BACKGROUND: AI-aided home stethoscopes offer the opportunity of continuous remote monitoring of cyst...

Predicting mother and newborn skin-to-skin contact using a machine learning approach.

BACKGROUND: Despite the known benefits of skin-to-skin contact (SSC), limited data exists on its imp...

The development of an artificial intelligence auto-segmentation tool for 3D volumetric analysis of vestibular schwannomas.

Linear and volumetric analysis are the typical methods to measure tumor size. 3D volumetric analysis...

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