Pediatrics

Machine learning prediction of malaria vaccine efficacy based on antibody profiles.

Immunization through repeated direct venous inoculation of Plasmodium falciparum (Pf) sporozoites (P...

NKUT: Dataset and Benchmark for Pediatric Mandibular Wisdom Teeth Segmentation.

Germectomy is a common surgery in pediatric dentistry to prevent the potential dangers caused by imp...

Perspectives on managing non-communicable diseases in pediatric health using artificial intelligence.

Identifying the risk of depression in a large sample of adolescents: An artificial neural network based on random forest.

BACKGROUND: This study aims to develop an artificial neural network (ANN) prediction model incorpora...

Machine learning identifies different related factors associated with depression and suicidal ideation in Chinese children and adolescents.

BACKGROUND: Depression and suicidal ideation often co-occur in children and adolescents, yet they po...

Artificial Intelligence in the Provision of Health Care: An American College of Physicians Policy Position Paper.

Internal medicine physicians are increasingly interacting with systems that implement artificial int...

Applying an explainable machine learning model might reduce the number of negative appendectomies in pediatric patients with a high probability of acute appendicitis.

The diagnosis of acute appendicitis and concurrent surgery referral is primarily based on clinical p...

Scaling the Idea of Opinion Leadership to Address Health Misinformation: The Case for "Health Communication AI".

There is strong evidence of the impact of opinion leaders in health promotion programs. Early work b...

Interaction between clinicians and artificial intelligence to detect fetal atrioventricular septal defects on ultrasound: how can we optimize collaborative performance?

OBJECTIVES: Artificial intelligence (AI) has shown promise in improving the performance of fetal ult...

Role of artificial-intelligence-assisted automated cardiac biometrics in prenatal screening for coarctation of aorta.

OBJECTIVE: Although remarkable strides have been made in fetal medicine and the prenatal diagnosis o...

Country-specific determinants for COVID-19 case fatality rate and response strategies from a global perspective: an interpretable machine learning framework.

BACKGROUND: There are significant geographic inequities in COVID-19 case fatality rates (CFRs), and ...

Investigation on ultrasound images for detection of fetal congenital heart defects.

Congenital heart defects (CHD) are one of the serious problems that arise during pregnancy. Early CH...

A computational clinical decision-supporting system to suggest effective anti-epileptic drugs for pediatric epilepsy patients based on deep learning models using patient's medical history.

BACKGROUND: Epilepsy, a chronic brain disorder characterized by abnormal brain activity that causes ...

Heart and great vessels segmentation in congenital heart disease via CNN and conditioned energy function postprocessing.

PURPOSE: The segmentation of the heart and great vessels in CT images of congenital heart disease (C...

Predicting autism traits from baby wellness records: A machine learning approach.

Timely identification of autism spectrum conditions is a necessity to enable children to receive the...

Growth period determination and color coordinates visual analysis of tomato using hyperspectral imaging technology.

Growth period determination and color coordinates prediction are essential for comparing postharvest...

Machine learning models for assessing risk factors affecting health care costs: 12-month exercise-based cardiac rehabilitation.

INTRODUCTION: Exercise-based cardiac rehabilitation (ECR) has proven to be effective and cost-effect...

Comparative analysis of machine learning versus traditional method for early detection of parental depression symptoms in the NICU.

INTRODUCTION: Neonatal intensive care unit (NICU) admission is a stressful experience for parents. N...

Screening and Identification of Neutrophil Extracellular Trap-related Diagnostic Biomarkers for Pediatric Sepsis by Machine Learning.

Neutrophil extracellular trap (NET) is released by neutrophils to trap invading pathogens and can le...

Machine learning model with output correction: Towards reliable bradycardia detection in neonates.

Bradycardia is a commonly occurring condition in premature infants, often causing serious consequenc...

Intelligent wearable olfactory interface for latency-free mixed reality and fast olfactory enhancement.

Olfaction feedback systems could be utilized to stimulate human emotion, increase alertness, provide...