AIMC Topic: Infant

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Intelligent diagnosis of Kawasaki disease from real-world data using interpretable machine learning models.

Hellenic journal of cardiology : HJC = Hellenike kardiologike epitheorese Aug 10, 2024
OBJECTIVE: This study aimed to leverage real-world electronic medical record data to develop interpretable machine learning models for diagnosis of Kawasaki disease while also exploring and prioritizing the significant risk factors.
Infant China Child, Preschool Child ROC Curve Mucocutaneous Lymph Node Syndrome Electronic Health Records Female Risk Factors Male Humans Machine Learning
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Diagnosis of Hirschsprung disease by analyzing acetylcholinesterase staining using artificial intelligence.

Journal of pediatric gastroenterology and nutrition Aug 9, 2024
OBJECTIVES: Classical Hirschsprung disease (HD) is defined by the absence of ganglion cells in the rectosigmoid colon. The diagnosis is made from rectal biopsy, which reveals the aganglionosis and the presence of cholinergic hyperinnervation. However...
Adolescent Child, Preschool Child Staining and Labeling Machine Learning Female Male Infant Rectum Biopsy Acetylcholinesterase Hirschsprung Disease Humans Artificial Intelligence
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Training and Comparison of nnU-Net and DeepMedic Methods for Autosegmentation of Pediatric Brain Tumors.

AJNR. American journal of neuroradiology Aug 9, 2024
BACKGROUND AND PURPOSE: Tumor segmentation is essential in surgical and treatment planning and response assessment and monitoring in pediatric brain tumors, the leading cause of cancer-related death among children. However, manual segmentation is tim...
Female Brain Neoplasms Male Infant Humans Imaging, Three-Dimensional Magnetic Resonance Imaging Image Interpretation, Computer-Assisted Multiparametric Magnetic Resonance Imaging Deep Learning Adolescent Child, Preschool Child
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Morphological Rule-Constrained Object Detection of Key Structures in Infant Fundus Image.

IEEE/ACM transactions on computational biology and bioinformatics Aug 9, 2024
The detection of optic disc and macula is an essential step for ROP (Retinopathy of prematurity) zone segmentation and disease diagnosis. This paper aims to enhance deep learning-based object detection with domain-specific morphological rules. Based ...
Macula Lutea Retinopathy of Prematurity Humans Algorithms Deep Learning Infant, Newborn Fundus Oculi Infant Image Interpretation, Computer-Assisted Optic Disk
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Deep learning-based automated bone age estimation for Saudi patients on hand radiograph images: a retrospective study.

BMC medical imaging Aug 1, 2024
PURPOSE: In pediatric medicine, precise estimation of bone age is essential for skeletal maturity evaluation, growth disorder diagnosis, and therapeutic intervention planning. Conventional techniques for determining bone age depend on radiologists' s...
Humans Neural Networks, Computer Retrospective Studies Female Hand Bones Adolescent Male Child, Preschool Infant Child Deep Learning Age Determination by Skeleton Saudi Arabia
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Bimodal machine learning model for unstable hips in infants: integration of radiographic images with automatically-generated clinical measurements.

Scientific reports Aug 1, 2024
Bimodal convolutional neural networks (CNNs) are frequently combined with patient information or several medical images to enhance the diagnostic performance. However, the technologies that integrate automatically generated clinical measurements with...
Infant Radiography Developmental Dysplasia of the Hip Humans Algorithms Neural Networks, Computer Female Machine Learning Infant, Newborn Male
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Predictive modeling and socioeconomic determinants of diarrhea in children under five in the Amhara Region, Ethiopia.

Frontiers in public health Aug 1, 2024
BACKGROUND: Diarrheal disease, characterized by high morbidity and mortality rates, continues to be a serious public health concern, especially in developing nations such as Ethiopia. The significant burden it imposes on these countries underscores t...
Infant Infant, Newborn Humans Logistic Models Child, Preschool Risk Factors Machine Learning Socioeconomic Factors Adult Health Surveys Female Ethiopia Male Diarrhea
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Using Advanced Convolutional Neural Network Approaches to Reveal Patient Age, Gender, and Weight Based on Tongue Images.

BioMed research international Aug 1, 2024
The human tongue has been long believed to be a window to provide important insights into a patient's health in medicine. The present study introduced a novel approach to predict patient age, gender, and weight inferences based on tongue images using...
Adult Male Neural Networks, Computer Middle Aged Image Processing, Computer-Assisted Female Humans Adolescent Infant Age Factors Aged Child, Preschool Body Weight Young Adult Child Tongue ROC Curve
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Exploring Machine Learning Algorithms to Predict Diarrhea Disease and Identify its Determinants among Under-Five Years Children in East Africa.

Journal of epidemiology and global health Jul 29, 2024
BACKGROUND: The second most common cause of death for children under five is diarrhea. Early Predicting diarrhea disease and identify its determinants (factors) using an advanced machine learning model is the most effective way to save the lives of c...
Humans Machine Learning Algorithms Female Child, Preschool Infant, Newborn Diarrhea Risk Factors Logistic Models Male Africa, Eastern Infant
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Communicating exploratory unsupervised machine learning analysis in age clustering for paediatric disease.

BMJ health & care informatics Jul 29, 2024
BACKGROUND: Despite the increasing availability of electronic healthcare record (EHR) data and wide availability of plug-and-play machine learning (ML) Application Programming Interfaces, the adoption of data-driven decision-making within routine hos...
Child Age Factors Cluster Analysis Unsupervised Machine Learning Male Infant Adolescent Child, Preschool Humans Electronic Health Records Female Infant, Newborn
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