AIMC Topic: Infant

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An artificial intelligence platform for the screening and managing of strabismus.

Eye (London, England) Jul 27, 2024
OBJECTIVES: Considering the escalating incidence of strabismus and its consequential jeopardy to binocular vision, there is an imperative demand for expeditious and precise screening methods. This study was to develop an artificial intelligence (AI) ...
Middle Aged Young Adult Infant Vision Screening Adult Adolescent Sensitivity and Specificity Child, Preschool Humans Male Child Artificial Intelligence Strabismus Female Vision, Binocular
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Development of machine learning models predicting mortality using routinely collected observational health data from 0-59 months old children admitted to an intensive care unit in Bangladesh: critical role of biochemistry and haematology data.

BMJ paediatrics open Jul 22, 2024
INTRODUCTION: Treatment in the intensive care unit (ICU) generates complex data where machine learning (ML) modelling could be beneficial. Using routine hospital data, we evaluated the ability of multiple ML models to predict inpatient mortality in a...
Child, Preschool Hospital Mortality ROC Curve Bangladesh Female Infant, Newborn Male Infant Machine Learning Retrospective Studies Intensive Care Units Humans
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Pediatric cardiac surgery: machine learning models for postoperative complication prediction.

Journal of anesthesia Jul 19, 2024
PURPOSE: Managing children undergoing cardiac surgery with cardiopulmonary bypass (CPB) presents a significant challenge for anesthesiologists. Machine Learning (ML)-assisted tools have the potential to enhance the recognition of patients at risk of ...
Cardiopulmonary Bypass Support Vector Machine Area Under Curve Cardiac Surgical Procedures Female Male Risk Assessment Postoperative Complications Infant Humans Child, Preschool Machine Learning Child Logistic Models
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Development of a diagnostic model for biliary atresia based on MMP7 and serological tests using machine learning.

Pediatric surgery international Jul 19, 2024
OBJECTIVE: To develop a machine learning diagnostic model based on MMP7 and other serological testing indicators for early and efficient diagnosis of biliary atresia (BA).
Humans Machine Learning Retrospective Studies Infant, Newborn Matrix Metalloproteinase 7 Infant Feces Biliary Atresia Serologic Tests
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Estimating infant age from skull X-ray images using deep learning.

Scientific reports Jul 18, 2024
This study constructed deep learning models using plain skull radiograph images to predict the accurate postnatal age of infants under 12 months. Utilizing the results of the trained deep learning models, it aimed to evaluate the feasibility of emplo...
Infant, Newborn Male Infant Deep Learning Image Processing, Computer-Assisted Radiography Skull Humans Neural Networks, Computer Female
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Diagnostic performance of an AI algorithm for the detection of appendicular bone fractures in pediatric patients.

European journal of radiology Jul 17, 2024
PURPOSE: To evaluate the diagnostic performance of an Artificial Intelligence (AI) algorithm, previously trained using both adult and pediatric patients, for the detection of acute appendicular fractures in the pediatric population on conventional X-...
Algorithms Child Retrospective Studies Humans Fractures, Bone Female Artificial Intelligence Radiography Sensitivity and Specificity Male Infant Adolescent Child, Preschool
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Accelerated cardiac magnetic resonance imaging using deep learning for volumetric assessment in children.

Pediatric radiology Jul 17, 2024
BACKGROUND: Ventricular volumetry using a short-axis stack of two-dimensional (D) cine balanced steady-state free precession (bSSFP) sequences is crucial in any cardiac magnetic resonance imaging (MRI) examination. This task becomes particularly chal...
Male Infant Deep Learning Adolescent Humans Retrospective Studies Female Magnetic Resonance Imaging, Cine Child, Preschool Child Heart Ventricles Image Interpretation, Computer-Assisted
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A machine learning artefact detection method for single-channel infant event-related potential studies.

Journal of neural engineering Jul 16, 2024
. Automated detection of artefact in stimulus-evoked electroencephalographic (EEG) data recorded in neonates will improve the reproducibility and speed of analysis in clinical research compared with manual identification of artefact. Some studies use...
Humans Machine Learning Algorithms Infant Electroencephalography Artifacts Evoked Potentials Female Infant, Newborn Reproducibility of Results Male
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Factors of acute respiratory infection among under-five children across sub-Saharan African countries using machine learning approaches.

Scientific reports Jul 9, 2024
Symptoms of Acute Respiratory infections (ARIs) among under-five children are a global health challenge. We aimed to train and evaluate ten machine learning (ML) classification approaches in predicting symptoms of ARIs reported by mothers among child...
Humans Machine Learning Female Africa South of the Sahara Respiratory Tract Infections Child, Preschool Infant, Newborn Acute Disease Male Air Pollution Infant Particulate Matter
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Artificial intelligence detects awareness of functional relation with the environment in 3 month old babies.

Scientific reports Jul 6, 2024
A recent experiment probed how purposeful action emerges in early life by manipulating infants' functional connection to an object in the environment (i.e., tethering an infant's foot to a colorful mobile). Vicon motion capture data from multiple inf...
Environment Deep Learning Awareness Humans Movement Neural Networks, Computer Artificial Intelligence Female Male Infant
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