Pediatrics

Research on the impact of artificial intelligence development on urban low-carbon transformation.

Scientific analysis of the impact of artificial intelligence (AI) development on urban low-carbon transformation has substantial practical implications for better fostering the development of AI and high-quality urbanization. Based on the panel data of 226 cities in China from 2012 to 2022, this study first designed a comprehensive evaluation index system for the development of AI and urban low-ca...

Generative AI for weakly supervised segmentation and downstream classification of brain tumors on MR images.

Segmenting abnormalities is a leading problem in medical imaging. Using machine learning for segmentation generally requires manually annotated segmentations, demanding extensive time and resources from radiologists. We propose a weakly supervised approach that utilizes binary image-level labels, which are much simpler to acquire, rather than manual annotations to segment brain tumors on magnetic ...

Closed circuit artificial ıntelligence model named morgaf for childhood onset systemic lupus erythematosus diagnosis.

Systemic Lupus Erythematosus (SLE) is a chronic, autoimmune disease characterized by multiple organ involvement and autoantibodies, and its diagnosis ...

Integrated artificial intelligence in healthcare and the patient's experience of care.

Healthcare is plagued with many problems that Artificial Intelligence (AI) can ameliorate or sometimes amplify. Regardless, AI is changing the way we ...

Decoding the diagnostic biomarkers of mitochondrial dysfunction related gene variants in pediatric T cell acute lymphoblastic leukemia.

Mitochondrial dysfunction is crucial in the pathogenesis and drug resistance of pediatric T-cell acute lymphoblastic leukemia (T-ALL), a malignant hem...

Machine learning-assisted decoding of temporal transcriptional dynamics via fluorescent timer.

Investigating the temporal dynamics of gene expression is crucial for understanding gene regulation across various biological processes. Using the Flu...

Machine learning to detect melanoma exploiting nuclei morphology and Spatial organization.

Cutaneous melanoma is one of the most lethal forms of skin cancer, and its incidence is increasing globally. Its diagnosis typically relies on manual ...

Activated cancer-associated fibroblasts correlate with poor survival and decreased lymphocyte infiltration in infiltrative type distal cholangiocarcinoma.

Cancer-associated fibroblasts promote tumor progression through growth facilitation, invasion, and immune evasion. This study investigated the impact ...

Development of a machine learning model to identify the predictors of the neonatal intensive care unit admission.

Scientists aim to create a system that can predict the likelihood of newborns being admitted to the neonatal intensive care unit (NICU) by combining v...

Expert-augmented machine learning for predicting extubation readiness in the pediatric intensive care unit.

BACKGROUND: Determining extubation readiness in pediatric intensive care units (PICU) is challenging. We used expert-augmented machine learning (EAML)...

Perceived worries in the adoption of artificial intelligence among nurses in neonatal intensive care units.

INTRODUCTION: Artificial Intelligence (AI) comprises computational algorithms designed to analyze data, learn patterns, and execute tasks traditionall...

Protocol for a randomized and a non-randomized controlled trial testing Daily Growth: a personalised 'ecological momentary intervention' parenting app for parents and carers of children aged 2-5 years.

BACKGROUND: Children's ability to regulate their emotions is a critical protective factor for early mental health and development and is strongly infl...

Artificial Intelligence in Palliative Care: A Scoping Review of Current Applications, Challenges, and Future Directions.

BackgroundArtificial Intelligence (AI) is increasingly integrated into healthcare systems, presenting opportunities to improve clinical outcomes. In t...

Artificial Intelligence Iterative Reconstruction for Dose Reduction in Pediatric Chest CT: A Clinical Assessment via Below 3 Years Patients With Congenital Heart Disease.

PURPOSE: To assess the performance of a newly introduced deep learning-based reconstruction algorithm, namely the artificial intelligence iterative re...

Modernizing Risk Adjustment in Health Care: A Position Paper of the American College of Physicians.

Risk adjustment is a critical component of health care reimbursement aimed at ensuring fair compensation on the basis of the characteristics of patien...

How does social support influence autonomous physical learning in adolescents? Evidence from a chain mediation and latent profile analysis.

PURPOSE: This study examines how social support influences adolescents' autonomous physical learning behavior, exploring the mediating roles of self-e...

[Artificial intelligence in preventive medicine for children and adolescents-applications and acceptance].

The use of artificial intelligence (AI) in pediatric and adolescent medicine offers numerous possibilities, particularly in the prevention of chronic ...

Electroencephalogram features support the retrogenesis hypothesis of Alzheimer's disease: Exploratory comparison of brain changes in aging and childhood.

BackgroundThe retrogenesis hypothesis (RH) suggests that the functional and cognitive decline observed in Alzheimer's disease dementia mirrors in reve...

A Review of Medical Oxygen Concentrators for Respiratory Applications.

Medical oxygen concentrators are vital apparatuses that deliver supplemental oxygen to persons with hypoxemia. This narrative review provides a review...

Integrated multi-omics reveals the impact of ruminal keystone bacteria and microbial metabolites on average daily gain in Xuzhou cattle.

UNLABELLED: The rumen microbiome plays a crucial role in determining the metabolic and digestive efficiency of livestock. Despite its crucial role, th...