AIMC Topic: Child

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An Efficient Acute Lymphoblastic Leukemia Screen Framework Based on Multi-Modal Deep Neural Network.

International journal of laboratory hematology
BACKGROUND: Acute lymphoblastic leukemia (ALL) is a leading cause of death among pediatric malignancies. Early diagnosis of ALL is crucial for minimizing misdiagnosis, improving survival rates, and ensuring the implementation of precise treatment pla...

Machine-learning-assisted Preoperative Prediction of Pediatric Appendicitis Severity.

Journal of pediatric surgery
PURPOSE: This study evaluates the effectiveness of machine learning (ML) algorithms for improving the preoperative diagnosis of acute appendicitis in children, focusing on the accurate prediction of the severity of disease.

Risk Prediction of Liver Injury in Pediatric Tuberculosis Treatment: Development of an Automated Machine Learning Model.

Drug design, development and therapy
PURPOSE: Drug-induced liver injury (DILI) is one of the most common and serious adverse drug reactions related to first-line anti-tuberculosis drugs in pediatric tuberculosis patients. This study aims to develop an automatic machine learning (AutoML)...

Using supervised machine learning and ICD10 to identify non-accidental trauma in pediatric trauma patients in the Maryland Health Services Cost Review Commission dataset.

Child abuse & neglect
BACKGROUND: Identifying non-accidental trauma (NAT) in pediatric trauma patients is challenging. We developed a machine learning model that uses demographic characteristics and ICD10 codes to detect the first diagnosis of NAT.

Deep Neural Network Analysis of the 12-Lead Electrocardiogram Distinguishes Patients With Congenital Long QT Syndrome From Patients With Acquired QT Prolongation.

Mayo Clinic proceedings
OBJECTIVE: To test whether an artificial intelligence (AI) deep neural network (DNN)-derived analysis of the 12-lead electrocardiogram (ECG) can distinguish patients with long QT syndrome (LQTS) from those with acquired QT prolongation.

Development of a model for measuring sagittal plane parameters in 10-18-year old adolescents with idiopathic scoliosis based on RTMpose deep learning technology.

Journal of orthopaedic surgery and research
PURPOSE: The study aimed to develop a deep learning model for rapid, automated measurement of full-spine X-rays in adolescents with Adolescent Idiopathic Scoliosis (AIS). A significant challenge in this field is the time-consuming nature of manual me...

Multi-center brain age prediction via dual-modality fusion convolutional network.

Medical image analysis
Accurate prediction of brain age is crucial for identifying deviations between typical individual brain development trajectories and neuropsychiatric disease progression. Although current research has made progress, the effective application of brain...

Predicting Age and Visual-Motor Integration Using Origami Photographs: Deep Learning Study.

JMIR formative research
BACKGROUND: Origami is a popular activity among preschool children and can be used by therapists as an evaluation tool to assess children's development in clinical settings. It is easy to implement, appealing to children, and time-efficient, requirin...

Multiple constraint network classification reveals functional brain networks distinguishing 0-back and 2-back task.

Canadian journal of experimental psychology = Revue canadienne de psychologie experimentale
Working memory is associated with general intelligence and is crucial for performing complex cognitive tasks. Neuroimaging investigations have recognized that working memory is supported by a distribution of activity in regions across the entire brai...

Early Identification of Language Disorders Using Natural Language Processing and Machine Learning: Challenges and Emerging Approaches.

Journal of speech, language, and hearing research : JSLHR
PURPOSE: Recent advances in artificial intelligence provide opportunities to capture and represent complex features of human language in a more automated manner, offering potential means of improving the efficiency of language assessment. This review...