Pediatrics

Artificial Intelligence Outcome Prediction in Neonates with Encephalopathy (AI-OPiNE).

Purpose To develop a deep learning algorithm to predict 2-year neurodevelopmental outcomes in neonat...

Analyzing factors of daily travel distances in Japan during the COVID-19 pandemic.

The global impact of the COVID-19 pandemic is widely recognized as a significant concern, with human...

Democratizing Congenital Heart Disease Management: The Potential for AI-Enabled Care and Necessary Future Directions.

Deep Learning-Based Electrocardiogram Analysis Predicts Biventricular Dysfunction and Dilation in Congenital Heart Disease.

BACKGROUND: Artificial intelligence-enhanced electrocardiogram (AI-ECG) analysis shows promise to de...

Development of a Data Model to Predict Nursing Workload Using Routine Clinical Data.

The effective management of human resources in nursing is fundamental to ensuring high-quality care....

Data for AI in Congenital Heart Defects: Systematic Review.

Congenital heart disease (CHD) represents a significant challenge in prenatal care due to low prenat...

Deep Learning-Based Prediction of Daily COVID-19 Cases Using X (Twitter) Data.

Due to the importance of COVID-19 control, innovative methods for predicting cases using social netw...

Dementia Ontology Development to Facilitate Collection of High-Quality Dementia Data.

The population of dementia patients is on the rise, as society undergoes rapid aging. This led to an...

User-Centered Development of Explanation User Interfaces for AI-Based CDSS: Lessons Learned from Early Phases.

This paper reports lessons learned during the early phases of the user-centered design process for a...

Assessment of readability, reliability, and quality of ChatGPT®, BARD®, Gemini®, Copilot®, Perplexity® responses on palliative care.

There is no study that comprehensively evaluates data on the readability and quality of "palliative ...

Frontoparietal and salience network synchronizations during nonsymbolic magnitude processing predict brain age and mathematical performance in youth.

The development and refinement of functional brain circuits crucial to human cognition is a continuo...

Artificial Intelligence in Perioperative Care: Opportunities and Challenges.

Artificial intelligence (AI) applications have great potential to enhance perioperative care. This p...

Development and Validation of an Interpretable Machine Learning Model for Early Prognosis Prediction in ICU Patients with Malignant Tumors and Hyperkalemia.

This study aims to develop and validate a machine learning (ML) predictive model for assessing morta...

TransCell: In Silico Characterization of Genomic Landscape and Cellular Responses by Deep Transfer Learning.

Gene expression profiling of new or modified cell lines becomes routine today; however, obtaining co...

HRV-based Monitoring of Neonatal Seizures with Machine Learning.

With the rapid development of machine learning (ML) in biomedical signal processing, ML-based neonat...

Learning Physiological Mechanisms that Predict Adverse Cardiovascular Events in Intensive Care Patients with Chronic Heart Disease.

Chronic heart disease is a burdensome, complex, and fatal condition. Learning the mechanisms driving...

Preliminary Experimental Validation of a Cable-Driven Joint System for Custom Orthoses.

Robot-assisted gait training has the potential to enhance gait therapy for children with mobility im...

Automated Intraoperative Visual Detection of Pediatric Epileptogenic Brain Lesions Using a Machine Learning Classifier.

450,000 children with epilepsy in the United States suffer lifelong disability and are at risk of su...

Improving Neonatal Care with AI: Class Weight Optimization for Respiratory Distress Syndrome Prediction in Very Low Birth Weight Infants.

In this study, we developed an AI model to predict Respiratory Distress Syndrome (RDS) in premature ...

Explainable AI (XAI) for Neonatal Pain Assessment via Influence Function Modification.

As machine learning increasingly plays a crucial role in various medical applications, the need for ...

Towards the development of a FAIR-compliant biomedical ontology for colorectal cancer.

Despite the widespread development of ontologies in many domains of healthcare, the field of colorec...