AIMC Topic: Infant

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Development and Validation of an Electronic Health Record-Based, Pediatric Acute Respiratory Distress Syndrome Subphenotype Classifier Model.

Pediatric critical care medicine : a journal of the Society of Critical Care Medicine and the World Federation of Pediatric Intensive and Critical Care Societies Mar 6, 2025
OBJECTIVE: To determine if hyperinflammatory and hypoinflammatory pediatric acute respiratory distress syndrome (PARDS) subphenotypes defined using serum biomarkers can be determined solely from electronic health record (EHR) data using machine learn...
Respiratory Distress Syndrome Child, Preschool Child Intensive Care Units, Pediatric ROC Curve Machine Learning Phenotype Biomarkers Retrospective Studies Electronic Health Records Female Male Infant Adolescent Humans
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Prediction of malnutrition in kids by integrating ResNet-50-based deep learning technique using facial images.

Scientific reports Mar 6, 2025
In recent times, severe acute malnutrition (SAM) in India is considered a serious issue as per UNICEF 2022 records. In that record, 35.5% of children under age 5 are stunted, 19.3% are wasted, and 32% are underweight. Malnutrition, defined as these t...
Body Mass Index Malnutrition Face Child, Preschool Humans Child India Female Image Processing, Computer-Assisted Male Infant Deep Learning
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Construction and validation of a predictive model for meningoencephalitis in pediatric scrub typhus based on machine learning algorithms.

Emerging microbes & infections Mar 5, 2025
To retrospectively analyze the clinical characteristics of pediatric scrub typhus (ST) with meningoencephalitis (STME) and to construct and validate predictive models using machine learning.Clinical data were collected from 100 cases of pediatric STM...
Doxycycline Infant Adolescent Child, Preschool Child Bayes Theorem Humans Anti-Bacterial Agents Azithromycin Machine Learning Algorithms Retrospective Studies Orientia tsutsugamushi Female Scrub Typhus Risk Factors Meningoencephalitis Male
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Exploring the achievements and forecasting of SDG 3 using machine learning algorithms: Bangladesh perspective.

PloS one Mar 4, 2025
BACKGROUND: Sustainable Development Goal 3 (SDG 3), focusing on ensuring healthy lives and well-being for all, holds global significance and is particularly vital for Bangladesh. Neonatal Mortality Rate (NMR), Under-5 Mortality Rate (U5MR), Maternal ...
Child, Preschool Bangladesh Forecasting Child Mortality Humans Maternal Mortality Female Infant Mortality Infant, Newborn Neural Networks, Computer Sustainable Development Infant Machine Learning Algorithms
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Development and validation of a deep learning algorithm for prediction of pediatric recurrent intussusception in ultrasound images and radiographs.

BMC medical imaging Mar 3, 2025
PURPOSES: To develop a predictive model for recurrent intussusception based on abdominal ultrasound (US) images and abdominal radiographs.
Humans Algorithms Retrospective Studies Female Child Ultrasonography ROC Curve Recurrence Intussusception Male Infant Deep Learning Child, Preschool Radiography, Abdominal
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Enhanced U-Net for Infant Brain MRI Segmentation: A (2+1)D Convolutional Approach.

Sensors (Basel, Switzerland) Feb 28, 2025
BACKGROUND: Infant brain tissue segmentation from MRI data is a critical task in medical imaging, particularly challenging due to the evolving nature of tissue contrasts in the early months of life. The difficulty increases as gray matter (GM) and wh...
Image Processing, Computer-Assisted Magnetic Resonance Imaging Cerebrospinal Fluid Datasets as Topic Humans White Matter Gray Matter Brain Spatio-Temporal Analysis Infant Deep Learning Convolutional Neural Networks Imaging, Three-Dimensional
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Development of an artificial intelligence-based multimodal diagnostic system for early detection of biliary atresia.

BMC medicine Feb 27, 2025
BACKGROUND: Early diagnosis of biliary atresia (BA) is crucial for improving patient outcomes, yet remains a significant global challenge. This challenge may be ameliorated through the application of artificial intelligence (AI). Despite the promise ...
Retrospective Studies Female Infant, Newborn Male Infant Deep Learning Ultrasonography Humans Early Diagnosis Artificial Intelligence Biliary Atresia Prospective Studies
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Machine learning for early diagnosis of Kawasaki disease in acute febrile children: retrospective cross-sectional study in China.

Scientific reports Feb 25, 2025
Early diagnosis of Kawasaki disease (KD) allows timely treatment to be initiated, thereby preventing coronary artery aneurysms in children. However, it is challenging due to the subjective nature of the diagnostic criteria. This study aims to develop...
Male Infant China Child, Preschool Child ROC Curve Mucocutaneous Lymph Node Syndrome Fever Early Diagnosis Humans Machine Learning Retrospective Studies Female Cross-Sectional Studies
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Deep Learning-Enhanced Ultra-high-resolution CT Imaging for Superior Temporal Bone Visualization.

Academic radiology Feb 24, 2025
RATIONALE AND OBJECTIVES: This study assesses the image quality of temporal bone ultra-high-resolution (UHR) Computed tomography (CT) scans in adults and children using hybrid iterative reconstruction (HIR) and a novel, vendor-specific deep learning-...
Female Aged Aged, 80 and over Young Adult Adult Humans Retrospective Studies Tomography, X-Ray Computed Adolescent Child, Preschool Child Male Radiographic Image Interpretation, Computer-Assisted Middle Aged Temporal Bone Infant Deep Learning
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AI-MET: A deep learning-based clinical decision support system for distinguishing multisystem inflammatory syndrome in children from endemic typhus.

Computers in biology and medicine Feb 22, 2025
The COVID-19 pandemic brought several diagnostic challenges, including the post-infectious sequelae multisystem inflammatory syndrome in children (MIS-C). Some of the clinical features of this syndrome can be found in other pathologies such as Kawasa...
Systemic Inflammatory Response Syndrome Decision Support Systems, Clinical Diagnosis, Differential Typhus, Endemic Flea-Borne Male Humans Infant COVID-19 Deep Learning Female Child, Preschool SARS-CoV-2 Child
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