Pediatrics

Latest AI and machine learning research in pediatrics for healthcare professionals.

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Application of the LDA model to identify topics in telemedicine conversations on the X social network.

The evolution experienced by global society, in the post-COVID 19 era, is marked by the quite obliga...

Development and validation of machine learning models for predicting extubation failure in patients undergoing cardiac surgery: a retrospective study.

Patients with multiple comorbidities and those undergoing complex cardiac surgery may experience ext...

Sustainable visions: unsupervised machine learning insights on global development goals.

The 2030 Agenda for Sustainable Development of the United Nations outlines 17 goals for countries of...

S-ketamine exposure in early postnatal period induces social deficit mediated by excessive microglial synaptic pruning.

The impact of general anesthetics on neurodevelopment is highly controversial in terms of clinical a...

Navigating artificial general intelligence development: societal, technological, ethical, and brain-inspired pathways.

This study examines the imperative to align artificial general intelligence (AGI) development with s...

Unraveling the power of NAP-CNB's machine learning-enhanced tumor neoantigen prediction.

In this study, we present a proof-of-concept classical vaccination experiment that validates the in ...

Prediction of Hypertension in the Pediatric Population Using Machine Learning and Transfer Learning: A Multicentric Analysis of the SAYCARE Study.

OBJECTIVE: To develop a machine learning (ML) model utilizing transfer learning (TL) techniques to p...

Integration of novel artificial intelligence tools in pediatric urologic practice.

PURPOSE OF REVIEW: There has been an explosion of creative uses of artificial intelligence (AI) in h...

Medical Misinformation in AI-Assisted Self-Diagnosis: Development of a Method (EvalPrompt) for Analyzing Large Language Models.

BACKGROUND: Rapid integration of large language models (LLMs) in health care is sparking global disc...

Factors associated with the development of severe asthma: A nationwide study (FINASTHMA).

BACKGROUND: Severe asthma presents a major challenge to health care and negatively affects the quali...

Development and validation of an interpretable machine learning model for predicting in-hospital mortality for ischemic stroke patients in ICU.

BACKGROUND: Timely and accurate outcome prediction is essential for clinical decision-making for isc...

Position-context additive transformer-based model for classifying text data on social media.

In recent years, the continuous increase in the growth of text data on social media has been a major...

AI-Driven decision-making for personalized elderly care: a fuzzy MCDM-based framework for enhancing treatment recommendations.

BACKGROUND: Global healthcare systems face enormous challenges due to the ageing population, demandi...

The Application of Machine Learning Models to Predict Stillbirths.

: This study aims to evaluate the predictive value of comprehensive data obtained in obstetric clini...

Development and Validation of an Electronic Health Record-Based, Pediatric Acute Respiratory Distress Syndrome Subphenotype Classifier Model.

OBJECTIVE: To determine if hyperinflammatory and hypoinflammatory pediatric acute respiratory distre...

GDF15, EGF, and Neopterin in Assessing Progression of Pediatric Chronic Kidney Disease Using Artificial Intelligence Tools-A Pilot Study.

Cell-mediated immunity and chronic inflammation are hallmarks of chronic kidney disease (CKD). Growt...

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