AIMC Topic: Child, Preschool

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Robust Machine Learning for Treatment Effects in Multilevel Observational Studies Under Cluster-level Unmeasured Confounding.

Psychometrika Oct 15, 2021
Recently, machine learning (ML) methods have been used in causal inference to estimate treatment effects in order to reduce concerns for model mis-specification. However, many ML methods require that all confounders are measured to consistently estim...
Causality Bias Confounding Factors, Epidemiologic Machine Learning Psychometrics Child, Preschool Longitudinal Studies Humans
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Limited generalizability of deep learning algorithm for pediatric pneumonia classification on external data.

Emergency radiology Oct 14, 2021
PURPOSE: (1) Develop a deep learning system (DLS) to identify pneumonia in pediatric chest radiographs, and (2) evaluate its generalizability by comparing its performance on internal versus external test datasets.
Neural Networks, Computer Algorithms Retrospective Studies Female Infant Deep Learning Child, Preschool Child Pneumonia Humans
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Image quality assessment of pediatric chest and abdomen CT by deep learning reconstruction.

BMC medical imaging Oct 10, 2021
BACKGROUND: Efforts to reduce the radiation dose have continued steadily, with new reconstruction techniques. Recently, image denoising algorithms using artificial neural networks, termed deep learning reconstruction (DLR), have been applied to CT im...
Radiation Dosage Signal-To-Noise Ratio Radiography, Thoracic Radiography, Abdominal Child Contrast Media Radiographic Image Interpretation, Computer-Assisted Artifacts Humans Retrospective Studies Tomography, X-Ray Computed Female Male Infant Deep Learning Adolescent Child, Preschool
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Investigation of a dysmorphic facial phenotype in patients with Gaucher disease types 2 and 3.

Molecular genetics and metabolism Oct 5, 2021
Gaucher disease (GD) is a rare lysosomal storage disorder that is divided into three subtypes based on presentation of neurological manifestations. Distinguishing between the types has important implications for treatment and counseling. Yet, patient...
Humans Adolescent Cohort Studies Child, Preschool Child ROC Curve Gaucher Disease Facial Recognition Musculoskeletal Abnormalities Infant, Newborn Young Adult Adult Male Infant Artificial Intelligence Software Phenotype Female
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Comparison of machine learning algorithms applied to symptoms to determine infectious causes of death in children: national survey of 18,000 verbal autopsies in the Million Death Study in India.

BMC public health Oct 4, 2021
BACKGROUND: Machine learning (ML) algorithms have been successfully employed for prediction of outcomes in clinical research. In this study, we have explored the application of ML-based algorithms to predict cause of death (CoD) from verbal autopsy r...
Humans Child, Preschool Child India Cause of Death Autopsy Machine Learning Algorithms Communicable Diseases Infant
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A Continuously Benchmarked and Crowdsourced Challenge for Rapid Development and Evaluation of Models to Predict COVID-19 Diagnosis and Hospitalization.

JAMA network open Oct 1, 2021
IMPORTANCE: Machine learning could be used to predict the likelihood of diagnosis and severity of illness. Lack of COVID-19 patient data has hindered the data science community in developing models to aid in the response to the pandemic.
Prognosis Female Infant, Newborn Hospitalization Aged Humans Machine Learning COVID-19 Algorithms Middle Aged Infant Severity of Illness Index Adolescent Child, Preschool Aged, 80 and over Young Adult Adult Male Benchmarking COVID-19 Testing Crowdsourcing Washington Clinical Decision Rules Child ROC Curve Models, Statistical Area Under Curve
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Artificial Intelligence Algorithm Improves Radiologist Performance in Skeletal Age Assessment: A Prospective Multicenter Randomized Controlled Trial.

Radiology Sep 28, 2021
Background Previous studies suggest that use of artificial intelligence (AI) algorithms as diagnostic aids may improve the quality of skeletal age assessment, though these studies lack evidence from clinical practice. Purpose To compare the accuracy ...
Radiologists Radiographic Image Interpretation, Computer-Assisted Age Determination by Skeleton Adolescent Child, Preschool Child Radiography Humans Artificial Intelligence Prospective Studies Female Reproducibility of Results Adult Sensitivity and Specificity Male Infant
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Identification of Sex and Age from Macular Optical Coherence Tomography and Feature Analysis Using Deep Learning.

American journal of ophthalmology Sep 25, 2021
PURPOSE: To develop deep learning models for identification of sex and age from macular optical coherence tomography (OCT) and to analyze the features for differentiation of sex and age.
Child Tomography, Optical Coherence Fundus Oculi Macula Lutea Humans Cross-Sectional Studies Deep Learning Child, Preschool
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From a Polish 3-Year-Old Boy Who Visited Maastricht to Automatic Detection Using Deep Learning: Brugada Syndrome Is Being Revolutionised.

The Canadian journal of cardiology Sep 24, 2021
Humans Male Brugada Syndrome Poland Deep Learning Child, Preschool Electrocardiography
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Combining multi-site magnetic resonance imaging with machine learning predicts survival in pediatric brain tumors.

Scientific reports Sep 23, 2021
Brain tumors represent the highest cause of mortality in the pediatric oncological population. Diagnosis is commonly performed with magnetic resonance imaging. Survival biomarkers are challenging to identify due to the relatively low numbers of indiv...
Image Processing, Computer-Assisted Bayes Theorem Neoplasm Grading Biopsy Survival Analysis Kaplan-Meier Estimate Magnetic Resonance Angiography Diffusion Magnetic Resonance Imaging Infant Adolescent Child, Preschool Child Infant, Newborn Brain Neoplasms Male Risk Assessment Humans Machine Learning Brain Female
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