Pediatrics

Accuracy of Diagnosis and Anticipation of Future Treatment in Pediatric Peripelvic Infections: The Role of Multisurgeon Review and Implications for Future Machine Learning Algorithms.

INTRODUCTION: MRI is commonly used to evaluate pelvic musculoskeletal infections. Limited "quick" MRI protocols enable timely imaging without intravenous contrast or sedation. This study examines the consistency of interpretation among pediatric orthopaedic surgeons when using quick versus full, contrast-enhanced MRI scans in cases of peripelvic musculoskeletal infection and explores these finding...

Artificial intelligence in surgical care within low-income and middle-income countries: a scoping review of development, validation, and deployment.

Artificial intelligence (AI) has the potential to expand access to high-quality surgical care in low-income and middle-income countries (LMICs), yet the extent and maturity of AI research in these settings remain unclear. We conducted a prospectively registered scoping review (osf.io/9PV6A) to synthesize primary evidence on the use of AI in LMIC surgical care. PubMed, Scopus, and Web of Science we...

Response of the authors to the letter to the editor regarding "Development of a machine learning-based predictive model for long-term adverse outcomes in neonatal bacterial meningitis".

Compact Involutional Transformer for Automated Detection of Pediatric Tooth Number Anomalies on Panoramic Radiographs.

Pediatric tooth number anomalies can compromise occlusion, craniofacial development, and long-term treatment planning. This study introduces the Compa...

The Effect of ChatGPT-Assisted Medication Dosage Calculation Training on Accuracy, Time, and Learning Satisfaction Among Nursing Students: A Quasi-Experimental Study.

Medication dosage calculation is a vital clinical skill essential for patient safety. However, many nursing students experience difficulties mastering...

Development and validation of stability prediction models for intracranial aneurysms based on ensemble learning algorithms.

OBJECTIVE: This study aims to develop and validate ensemble learning models based on pre-rupture or pre-growth images andmultiple features to predict ...

Radiomics in fetal brain MRI: a narrative review.

Fetal MRI has emerged as a crucial supplement to prenatal ultrasonography in the evaluation of the developing brain and in identifying congenital defe...

Zero Echo Time Magnetic Resonance Imaging of the Spine.

Zero echo time magnetic resonance imaging is an ultrashort echo time technique that enables computed tomography-like visualization of cortical and tra...

Mining antibody functionality via AI-guided structural landscape profiling.

Despite substantial progress in single-cell screening techniques, antibody (Ab) repertoires still remain enigmatic. Here we show that Ab sequences can...

Development and Validation of an Automated Pediatric Cancer Staging Calculator Using the Toronto Pediatric Cancer Stage Guidelines.

BACKGROUND: Pediatric cancer stage at diagnosis is critical for prognosis and research comparisons. The Toronto Pediatric Cancer Stage Guidelines stan...

Integrating artificial intelligence into nursing practice: Development and clinical evaluation of the NURSYA care model based on Levine's Conservation Principles.

BACKGROUND: Although artificial intelligence (AI) is increasingly used in healthcare, its integration with established nursing theories remains limite...

An artificial intelligence approach to support adolescent suicide prevention initiatives in the United States.

Adolescent suicide remains a critical public health issue in the United States, with complex, interrelated risk and protective factors operating acros...

Foodie traps within facebook cannabis promotional posts: Deploying multimodal deep learning AIs to monitor audience engagement.

BACKGROUND: Cannabis marketing has flourished due to the legalization of recreational cannabis across multiple U.S. states, particularly on social med...

Beyond benchmarks of IUGC: Rethinking requirements of deep learning method for intrapartum ultrasound biometry from fetal ultrasound videos.

A significant proportion (45%) of maternal deaths, neonatal deaths, and stillbirths occur during the intrapartum phase, particularly prevalent in low-...

The economic imperative of artificial intelligence in maternal and neonatal health: a review of evaluation benefits, frameworks, challenges, future perspectives, and limitations.

Integrating artificial intelligence (AI) into maternal and neonatal health (MNH) offers significant opportunities for enhancing patient care through a...

The acquisition of native language phonotactics: Integrating insights from machine learning, and adult and infant experiments.

Languages differ in their phonotactics - the restrictions on positions and sequencing of segments. Many phonotactic restrictions are specific to a giv...

Certainty Language Use in Pediatric Radiology: A Single-Institution Analysis.

BACKGROUND: Radiologists often employ diagnostic certainty phrases (DCPs) to convey levels of confidence in imaging interpretations. Prior research in...

Computational Innovations in Cancer Research and How Computing is Transforming Drug Discovery and Development: A Review.

INTRODUCTION: Cancer is a major global health concern, causing millions of deaths each year due to the uncontrolled growth and spread of abnormal cell...

Letter to the editor regarding "Development of a machine learning-based predictive model for long-term adverse outcomes in neonatal bacterial meningitis".

Federated clinical concept and disease semantic learning for congenital heart disease diagnosis.

Effective first-trimester screening for congenital heart disease (CHD) remains an unmet clinical need, hindered by technical constraints and the lack ...