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Machine Learning-based Prediction of Blood Stream Infection in Pediatric Febrile Neutropenia.

Journal of pediatric hematology/oncology
OBJECTIVES: This study aimed to develop machine learning (ML) prediction models for identifying bloodstream infection (BSI) and septic shock (SS) in pediatric patients with cancer who presenting febrile neutropenia (FN) at emergency department (ED) v...

Deep caries detection using deep learning: from dataset acquisition to detection.

Clinical oral investigations
OBJECTIVES: The study aims to address the global burden of dental caries, a highly prevalent disease affecting billions of individuals, including both children and adults. Recognizing the significant health challenges posed by untreated dental caries...

Estimating Ground Reaction Forces from Gait Kinematics in Cerebral Palsy: A Convolutional Neural Network Approach.

Annals of biomedical engineering
PURPOSE: While gait analysis is essential for assessing neuromotor disorders like cerebral palsy (CP), capturing accurate ground reaction force (GRF) measurements during natural walking presents challenges, particularly due to variations in gait patt...

MediLite3DNet: A lightweight network for segmentation of nasopharyngeal airways.

Medical & biological engineering & computing
The precise segmentation and three-dimensional reconstruction of the nasopharyngeal airway are crucial for the diagnosis and treatment of adenoid hypertrophy in children. However, traditional methods face challenges such as information loss and low c...

Artificial Intelligence Applications to Measure Food and Nutrient Intakes: Scoping Review.

Journal of medical Internet research
BACKGROUND: Accurate measurement of food and nutrient intake is crucial for nutrition research, dietary surveillance, and disease management, but traditional methods such as 24-hour dietary recalls, food diaries, and food frequency questionnaires are...

AI-assisted patient education: Challenges and solutions in pediatric kidney transplantation.

Patient education and counseling
We are writing in response to the recent publication on the use of artificial intelligence, particularly ChatGPT, in generating educational materials for pediatric kidney transplant patients (Patient Education and Counseling, Volume 129, 2024). The s...

Assessing greenspace and cardiovascular health through deep-learning analysis of street-view imagery in a cohort of US children.

Environmental research
BACKGROUND: Accurately capturing individuals' experiences with greenspace at ground-level can provide valuable insights into their impact on children's health. However, most previous research has relied on coarse satellite-based measurements.

Parental perspectives following the implementation of advanced hybrid closed-loop therapy in children and adolescents with type 1 diabetes and elevated glycaemia.

Diabetic medicine : a journal of the British Diabetic Association
AIMS: To identify from a parental perspective facilitators and barriers of effective implementation of advanced hybrid closed-loop (AHCL) therapy in children and adolescents with type 1 diabetes (T1D) with elevated glycaemia.

Predictive analysis of bullying victimization trajectory in a Chinese early adolescent cohort based on machine learning.

Journal of affective disorders
BACKGROUND: The development of bullying victimization among adolescents displays significant individual variability, with general, group-based interventions often proving insufficient for partial victims. This study aimed to conduct a machine learnin...