Pediatrics

Influences of growth media and culture time on the SERS spectral patterns of three common pathogenic bacteria: a comparative analysis.

Surface-enhanced Raman spectroscopy (SERS) has emerged as a powerful tool for clinical microorganism identification, offering significant advantages over traditional culture-based methods, including minimal sample requirements, rapid detection, and operational simplicity. However, bacterial SERS spectra are subject to variations due to various experimental factors. To evaluate the influence of two...

Artificial Intelligence and Radiogenomics for Pediatric CNS Neoplasms.

The 5th edition of the WHO CNS tumor classification (2021) emphasizes molecular alterations, especially in pediatric tumors, integrating histology with molecular profiling for precise diagnosis. Advances like DNA methylation profiling and Next Generation Sequencing have refined tumor subtypes, influencing targeted therapies. Radiogenomics correlates imaging features with genetic profiles, enabling...

Hybridized artificial intelligence system for reducing neonatal mortality in Nigeria.

BACKGROUND: Neonatal diseases represent the leading cause of death in Nigeria, ranking the country second globally in neonatal mortality rates. Early ...

A Window Into Vulnerability and Support: At-Risk Mothers' Perinatal Experiences and Perspectives on mHealth-Based Care.

AIM: To examine the perinatal experiences of at-risk mothers and their engagement with mobile-health-based care. DESIGN: A qualitative descriptive stu...

Performance of machine learning algorithms in predicting the need for surgical fixation in pediatric craniomaxillofacial trauma.

Machine learning offers a novel approach to improve surgical triage in pediatric craniomaxillofacial trauma, where decision-making often relies on cli...

The Pediatric Surgeon's AI Toolbox: How Large Language Models Like ChatGPT Are Simplifying Practice and Expanding Global Access.

INTRODUCTION: Pediatric surgeons face substantial administrative workload. Large language models (LLMs) may streamline documentation, family communica...

AI in Robotic-assisted Pediatric Surgery: Current Applications and Future Directions.

BACKGROUND: Artificial intelligence (AI) is increasingly integrated into surgical practice, offering enhanced decision-making, precision, and workflow...

Nodular Growths of NF2 -Related Schwannomatosis Vestibular Schwannoma: Clinical and Therapeutical Consequences.

BACKGROUND AND OBJECTIVES: Neurofibromatosis type 2-related schwannomatosis ( NF2 -SWN) is marked by the growth of bilateral vestibular schwannoma (VS...

Evaluation of image quality in pediatric portable chest radiographs using AI-based noise reduction and edge enhancement.

PURPOSE: To evaluate the image quality of pediatric portable chest radiographs processed using a deep learning-based noise reduction (NR) algorithm im...

Prognostic prediction of hepatoblastoma in children: development and validation of machine learning models-an SEER-based study.

Hepatoblastoma (HB) is the most common primary malignant liver tumor in children. Although the incidence is low, it is a serious threat to children's ...

Cervical cancer diagnostics: non-coding RNAs and biosensors to AI-derived methods.

Cervical cancer ranks fourth in terms of cancer mortality among women. The most important risk factor for cervical cancer is infection with HPV 16 and...

Health Care Ramifications of Pervasive Direct-to-Consumer Prescription Drug Advertising.

Direct-to-consumer (DTC) advertisements for prescription drugs are an enduring feature of the US media landscape. These ads are costly (>$8 billion ex...

Anesthesia and mitochondria: balancing toxicity and protection through emerging therapeutic strategies.

Anesthesia is a cornerstone of modern surgical practice, enabling interventions by deliberately modulating nociception and consciousness-from localize...

When AI Joins the Social Media Conversation: Exploring the Impact of Simulated AI-Assisted Comments on Health Risk Perceptions and Behaviors.

Misinformation on social media has long been a pressing concern, and its spread is often exacerbated by social endorsement metrics such as likes and s...

Predicting treatment pathways in Class II malocclusion patients using machine learning: A comparative study of four algorithms for classifying camouflage, growth modulation, and surgical decisions.

OBJECTIVES: The aim of this study was to develop a machine-learning model to assist in treatment decision-making for surgery, camouflage, and growth m...

Electrochemical sensors revolutionize plant nitrogen monitoring: Real-time, in situ detection for precision agriculture.

Driven by the dual imperatives of global food security and agricultural sustainability, dynamic plant nitrogen monitoring technology has emerged as a ...

Regulating AI in Nursing and Healthcare: Ensuring Safety, Equity, and Accessibility in the Era of Federal Innovation Policy.

The rapid integration of artificial intelligence in healthcare, accelerated by the Trump administration's 2025 AI Action Plan and private sector innov...

Development and validation of a prognostic model and risk calculator for the estimation of bipolar-spectrum disorder risk in hospitalised adolescents with non-psychotic/non-bipolar mental disorders.

We aimed to develop and validate a risk estimation model for developing bipolar-spectrum disorders (BSD) in psychiatrically hospitalized adolescents b...

Automated detection of neonatal pulmonary hypertension in echocardiograms with a deep learning model.

BACKGROUND: In infants, pulmonary hypertension (PH) increases morbidity and mortality. Echocardiography, though standard, is time- and expertise-deman...

Explainable AI: Ethical Frameworks, Bias, and the Necessity for Benchmarks.

Artificial intelligence (AI) is increasingly integrated into pediatric healthcare, offering opportunities to improve diagnostic accuracy and clinical ...