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...

Prediction of Epidermal Growth Factor Receptor Mutation Subtypes in Non-Small Cell Lung Cancer From Hematoxylin and Eosin-Stained Slides Using Deep Learning.

Accurate assessment of epidermal growth factor receptor (EGFR) mutation status and subtype is critic...

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...

Semi-supervised learning framework with shape encoding for neonatal ventricular segmentation from 3D ultrasound.

BACKGROUND: Three-dimensional (3D) ultrasound (US) imaging has shown promise in non-invasive monitor...

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 ...

Dynamic and Transdiagnostic Risk Calculator Based on Natural Language Processing for the Prediction of Psychosis in Secondary Mental Health Care: Development and Internal-External Validation Cohort Study.

BACKGROUND: Automatic transdiagnostic risk calculators can improve the detection of individuals at r...

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...

Advances in artificial intelligence for drug delivery and development: A comprehensive review.

Artificial intelligence (AI) has emerged as a powerful tool to revolutionize the healthcare sector, ...

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...

The Millennia-Long Development of Drugs Associated with the 80-Year-Old Artificial Intelligence Story: The Therapeutic Big Bang?

The journey of drug discovery (DD) has evolved from ancient practices to modern technology-driven ap...

A fully automated classification of third molar development stages using deep learning.

Accurate classification of tooth development stages from orthopantomograms (OPG) is crucial for dent...

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...

Beyond Shared Decision-Making: Integrating Coproduction, Learning Health Systems, Artificial Intelligence, and Workforce Development for Patient-Centered Care.

Machine learning-based surrogate modelling of a robust, sustainable development goal (SDG)-compliant land-use future for Australia at high spatial resolution.

We developed a high-resolution machine learning based surrogate model to identify a robust land-use ...

An ethical assessment of professional opinions on concerns, chances, and limitations of the implementation of an artificial intelligence-based technology into the geriatric patient treatment and continuity of care.

With the introduction of an artificial intelligence-based dashboard into the clinic, the project SUR...

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...

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