Pediatrics

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

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Artificial intelligence in assessing progression of age-related macular degeneration.

The human population is steadily growing with increased life expectancy, impacting the prevalence of...

Whole Slide Imaging, Artificial Intelligence, and Machine Learning in Pediatric and Perinatal Pathology: Current Status and Future Directions.

The integration of artificial intelligence (AI) into healthcare is becoming increasingly mainstream....

Artificial intelligence: a primer for pediatric radiologists.

Artificial intelligence (AI) is increasingly recognized for its transformative potential in radiolog...

Random Forest Prognostication of Survival and 6-Month Outcome in Pediatric Patients Following Decompressive Craniectomy for Traumatic Brain Injury.

BACKGROUND: There is a dearth of literature regarding prognostic and predictive factors for outcome ...

AI for Analyzing Mental Health Disorders Among Social Media Users: Quarter-Century Narrative Review of Progress and Challenges.

BACKGROUND: Mental health disorders are currently the main contributor to poor quality of life and y...

AFSleepNet: Attention-Based Multi-View Feature Fusion Framework for Pediatric Sleep Staging.

The widespread prevalence of sleep problems in children highlights the importance of timely and accu...

Deep learning-based models for preimplantation mouse and human embryos based on single-cell RNA sequencing.

The rapid growth of single-cell transcriptomic technology has produced an increasing number of datas...

Analysis of the impact of deep learning know-how and data in modelling neonatal EEG.

The performance gains achieved by deep learning models nowadays are mainly attributed to the usage o...

Machine learning algorithms for prediction of measles one vaccination dropout among 12-23 months children in Ethiopia.

INTRODUCTION: Despite the availability of a safe and effective measles vaccine in Ethiopia, the coun...

Glottic opening detection using deep learning for neonatal intubation with video laryngoscopy.

OBJECTIVE: This study aimed to develop an artificial intelligence (AI) method to augment video laryn...

Recommendations for the Development of Artificial Intelligence Applications for the Retail Level.

Some of the early applications of artificial intelligence (AI) for food safety appear to be intended...

Development of a Deep Learning Model for Classification of Hepatic Steatosis from Clinical Standard Ultrasound.

OBJECTIVE: Early detection and monitoring of hepatic steatosis can help establish appropriate preven...

Machine learning-based models for prediction of survival in medulloblastoma: a systematic review and meta-analysis.

BACKGROUND: Medulloblastoma (MB) is the pediatric population's most frequent malignant intracranial ...

MultiADE: A Multi-domain benchmark for Adverse Drug Event extraction.

OBJECTIVE: Active adverse event surveillance monitors Adverse Drug Events (ADE) from different data ...

A comparative study to elucidate factors explaining willingness to use home-care robots in Japan, Ireland, and Finland.

The implementation of home-care robots is sometimes unsuccessful. This study aimed to explore factor...

Subjective well-being of children with special educational needs: Longitudinal predictors using machine learning.

Children with special educational needs (SEN) are a diverse group facing numerous challenges related...

Applying machine learning to understand the role of social-emotional skills on subjective well-being and physical health.

Social-emotional skills are vital for individual development, yet research on which skills most effe...

Image-based deep learning in diagnosing mycoplasma pneumonia on pediatric chest X-rays.

BACKGROUND: Correctly diagnosing and accurately distinguishing mycoplasma pneumonia in children has ...

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