AIMC Topic: Child, Preschool
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An integrated machine learning model enhances delayed graft function prediction in pediatric renal transplantation from deceased donors.
BMC medicine
Sep 20, 2024
BACKGROUND: Kidney transplantation is the optimal renal replacement therapy for children with end-stage renal disease; however, delayed graft function (DGF), a common post-operative complication, may negatively impact the long-term outcomes of both t...
Children Are Not Small Adults: Addressing Limited Generalizability of an Adult Deep Learning CT Organ Segmentation Model to the Pediatric Population.
Journal of imaging informatics in medicine
Sep 19, 2024
Deep learning (DL) tools developed on adult data sets may not generalize well to pediatric patients, posing potential safety risks. We evaluated the performance of TotalSegmentator, a state-of-the-art adult-trained CT organ segmentation model, on a s...
Artificial intelligence in paediatric head trauma: enhancing diagnostic accuracy for skull fractures and brain haemorrhages.
Neurosurgical review
Sep 19, 2024
Pediatric head trauma is a significant cause of morbidity and mortality, with children, particularly those under two years old, being more susceptible to skull fractures due to their unique physiological and developmental characteristics. A recent st...
DentAge: Deep learning for automated age prediction using panoramic dental X-ray images.
Journal of forensic sciences
Sep 18, 2024
Age estimation plays a crucial role in various fields, including forensic science and anthropology. This study aims to develop and validate DentAge, a deep-learning model for automated age prediction using panoramic dental X-ray images. DentAge was t...
An automated framework for pediatric hip surveillance and severity assessment using radiographs.
International journal of computer assisted radiology and surgery
Sep 16, 2024
PURPOSE: Hip dysplasia is the second most common orthopedic condition in children with cerebral palsy (CP) and may result in disability and pain. The migration percentage (MP) is a widely used metric in hip surveillance, calculated based on an anteri...
Quantitative assessment of brain structural abnormalities in children with autism spectrum disorder based on artificial intelligence automatic brain segmentation technology and machine learning methods.
Psychiatry research. Neuroimaging
Sep 16, 2024
RATIONALE AND OBJECTIVES: To explore the characteristics of brain structure in Chinese children with autism spectrum disorder (ASD) using artificial intelligence automatic brain segmentation technique, and to diagnose children with ASD using machine ...
Machine learning-based evaluation of prognostic factors for mortality and relapse in patients with acute lymphoblastic leukemia: a comparative simulation study.
BMC medical informatics and decision making
Sep 16, 2024
BACKGROUND: Predicting mortality and relapse in children with acute lymphoblastic leukemia (ALL) is crucial for effective treatment and follow-up management. ALL is a common and deadly childhood cancer that often relapses after remission. In this stu...
Predictive performance of urinalysis for urine culture results according to causative microorganisms: an integrated analysis with artificial intelligence.
Journal of clinical microbiology
Sep 12, 2024
Urinary tract infections (UTIs) are pervasive and prevalent in both community and hospital settings. Recent trends in the changes of the causative microorganisms in these infections could affect the effectiveness of urinalysis (UA). We aimed to evalu...
CONSTRUCTING A DIAGNOSTIC PREDICTION MODEL TO ESTIMATE THE SEVERE RESPIRATORY SYNCYTIAL VIRUS PNEUMONIA IN CHILDREN BASED ON MACHINE LEARNING.
Shock (Augusta, Ga.)
Sep 11, 2024
Background : Severe respiratory syncytial virus (RSV) pneumonia is a leading cause of hospitalization and morbidity in infants and young children. Early identification of severe RSV pneumonia is crucial for timely and effective treatment by pediatric...
Development and validation of machine-learning models of diet management for hyperphenylalaninemia: a multicenter retrospective study.
BMC medicine
Sep 11, 2024
BACKGROUND: Assessing dietary phenylalanine (Phe) tolerance is crucial for managing hyperphenylalaninemia (HPA) in children. However, traditionally, adjusting the diet requires significant time from clinicians and parents. This study aims to investig...
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