Pediatrics

Primary care physicians' perceptions of artificial intelligence systems in the care of adolescents' mental health.

BACKGROUND: Given that mental health problems in adolescence may have lifelong impacts, the role of ...

Editorial Comment: The Radiologist's Role in Artificial Intelligence for Pediatric Oncologic Imaging.

Optimizing vancomycin dosing in pediatrics: a machine learning approach to predict trough concentrations in children under four years of age.

BACKGROUND: Vancomycin trough concentration is closely associated with clinical efficacy and toxicit...

Christian anthropology-based contributions to the ethics of socially assistive robots in care for older adults.

Our society, in general, and health care, in particular, faces notable challenges due to the emergen...

Prediction of sustained opioid use in children and adolescents using machine learning.

BACKGROUND: Opioid misuse in the paediatric population is understudied. This study aimed to develop ...

A Kernelized Classification Approach for Cancer Recognition Using Markovian Analysis of DNA Structure Patterns as Feature Mining.

Nucleotide-based molecules called DNA and RNA are essential for several biological processes that af...

Video-based assessments of activities of daily living: generating real-world evidence in pediatric rare diseases.

INTRODUCTION: Preserving function and independence to perform activities of daily living (ADL) is cr...

Identification of Multiclass Pediatric Low-Grade Neuroepithelial Tumor Molecular Subtype with ADC MR Imaging and Machine Learning.

BACKGROUND AND PURPOSE: Molecular biomarker identification increasingly influences the treatment pla...

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 ...

Development and deployment of a histopathology-based deep learning algorithm for patient prescreening in a clinical trial.

Accurate identification of genetic alterations in tumors, such as Fibroblast Growth Factor Receptor,...

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...