Pediatrics

Latest AI and machine learning research in pediatrics for healthcare professionals.

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Digital triage: Novel strategies for population health management in response to the COVID-19 pandemic.

The COVID-19 pandemic has created unique challenges for the U.S. healthcare system due to the stagge...

Fast body part segmentation and tracking of neonatal video data using deep learning.

Photoplethysmography imaging (PPGI) for non-contact monitoring of preterm infants in the neonatal in...

Prediction of obstetrical and fetal complications using automated electronic health record data.

An increasing number of delivering women experience major morbidity and mortality. Limited work has ...

Writhing Movement Detection in Newborns on the Second and Third Day of Life Using Pose-Based Feature Machine Learning Classification.

Observation of neuromotor development at an early stage of an infant's life allows for early diagnos...

The Effectiveness of Artificial Intelligence Conversational Agents in Health Care: Systematic Review.

BACKGROUND: The high demand for health care services and the growing capability of artificial intell...

A Racially Unbiased, Machine Learning Approach to Prediction of Mortality: Algorithm Development Study.

BACKGROUND: Racial disparities in health care are well documented in the United States. As machine l...

Predicting brain age with complex networks: From adolescence to adulthood.

In recent years, several studies have demonstrated that machine learning and deep learning systems c...

Artificial intelligence in drug discovery and development.

Artificial intelligence-integrated drug discovery and development has accelerated the growth of the ...

Regulatory Frameworks for Development and Evaluation of Artificial Intelligence-Based Diagnostic Imaging Algorithms: Summary and Recommendations.

Although artificial intelligence (AI)-based algorithms for diagnosis hold promise for improving care...

Development of a prognostic model for mortality in COVID-19 infection using machine learning.

Coronavirus disease 2019 (COVID-19) is a novel disease resulting from infection with severe acute re...

Towards Automated Emotion Classification of Atypically and Typically Developing Infants.

The World Health Organization estimates that 15 million infants are born preterm every year [1]. Thi...

Deep transfer learning for reducing health care disparities arising from biomedical data inequality.

As artificial intelligence (AI) is increasingly applied to biomedical research and clinical decision...

Robust deep learning classification of adamantinomatous craniopharyngioma from limited preoperative radiographic images.

Deep learning (DL) is a widely applied mathematical modeling technique. Classically, DL models utili...

Noise reduction approach in pediatric abdominal CT combining deep learning and dual-energy technique.

OBJECTIVES: To evaluate the image quality of low iodine concentration, dual-energy CT (DECT) combine...

Automatic segmentation, classification, and follow-up of optic pathway gliomas using deep learning and fuzzy c-means clustering based on MRI.

PURPOSE: Optic pathway gliomas (OPG) are low-grade pilocytic astrocytomas accounting for 3-5% of ped...

Deep neural networks detect suicide risk from textual facebook posts.

Detection of suicide risk is a highly prioritized, yet complicated task. Five decades of research ha...

Prediction and analysis of Corona Virus Disease 2019.

The outbreak of Corona Virus Disease 2019 (COVID-19) in Wuhan has significantly impacted the economy...

Machine learning-based analysis of adolescent gambling factors.

BACKGROUND AND AIMS: Problem gambling among adolescents has recently attracted attention because of ...

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