AIMC Topic: Child, Preschool

Clear Filters Showing 71 to 80 of 1285 articles

Development and Validation of a Novel Prediction Model for Hearing Loss From Cisplatin Chemotherapy.

Journal of clinical oncology : official journal of the American Society of Clinical Oncology
PURPOSE: Cisplatin treats many common tumors but causes permanent and debilitating hearing loss (HL). The objective of this study was to develop and externally validate a predictive model of HL in cisplatin-treated children and adolescent cancer surv...

Behavior recognition technology based on deep learning used in pediatric behavioral audiometry.

Scientific reports
This study aims to explore the feasibility and accuracy of deep learning-based pediatric behavioral audiometry. The research provides a dedicated pediatric posture detection dataset, which contains a large number of video clips from children's behavi...

Automatic ultrasound image alignment for diagnosis of pediatric distal forearm fractures.

International journal of computer assisted radiology and surgery
PURPOSE: The study aims to develop an automatic method to align ultrasound images of the distal forearm for diagnosing pediatric fractures. This approach seeks to bypass the reliance on X-rays for fracture diagnosis, thereby minimizing radiation expo...

Empowering Data Sharing in Neuroscience: A Deep Learning Deidentification Method for Pediatric Brain MRIs.

AJNR. American journal of neuroradiology
BACKGROUND AND PURPOSE: Privacy concerns, such as identifiable facial features within brain scans, have hindered the availability of pediatric neuroimaging data sets for research. Consequently, pediatric neuroscience research lags adult counterparts,...

Machine Learning for Predicting Critical Events Among Hospitalized Children.

JAMA network open
IMPORTANCE: Unrecognized deterioration among hospitalized children is associated with a high risk of mortality and morbidity. The current approach to pediatric risk stratification is fragmented, as each hospital unit (emergency, ward, or intensive ca...

Automated extraction of functional biomarkers of verbal and ambulatory ability from multi-institutional clinical notes using large language models.

Journal of neurodevelopmental disorders
BACKGROUND: Functional biomarkers in neurodevelopmental disorders, such as verbal and ambulatory abilities, are essential for clinical care and research activities. Treatment planning, intervention monitoring, and identifying comorbid conditions in i...

Clinical assessment of the criticality index - dynamic, a machine learning prediction model of future care needs in pediatric inpatients.

PloS one
OBJECTIVE: To assess patient characteristics and care factors that are associated with correct and incorrect predictions of future care locations (ICU vs. non-ICU) by the Criticality Index-Dynamic (CI-D), with the goal of enhancing the CI-D.

Machine learning for predicting medical outcomes associated with acute lithium poisoning.

Scientific reports
The use of machine learning algorithms and artificial intelligence in medicine has attracted significant interest due to its ability to aid in predicting medical outcomes. This study aimed to evaluate the effectiveness of the random forest algorithm ...

Modeling the number of new cases of childhood type 1 diabetes using Poisson regression and machine learning methods; a case study in Saudi Arabia.

PloS one
Diabetes mellitus stands out as one of the most prevalent chronic conditions affecting pediatric populations. The escalating incidence of childhood type 1 diabetes (T1D) globally is a matter of increasing concern. Developing an effective model that l...

Effect of pregnancy and infancy exposure to outdoor particulate matter (PM, PM, PM) and SO on childhood pneumonia in preschool children in Taiyuan City, China.

Environmental pollution (Barking, Essex : 1987)
There is currently a paucity of research on the effects of early life exposure to particulate matter (PM) of various size fractions on pneumonia in preschool-aged children. We explored the connections between antenatal and postnatal exposure to atmos...