Pediatrics

An Explainable and Conformal AI Model to Detect Temporomandibular Joint Involvement in Children Suffering from Juvenile Idiopathic Arthritis.

Juvenile idiopathic arthritis (JIA) is the most common rheumatic disease during childhood and adoles...

Stepwise Transfer Learning for Expert-level Pediatric Brain Tumor MRI Segmentation in a Limited Data Scenario.

Purpose To develop, externally test, and evaluate clinical acceptability of a deep learning pediatri...

Safe and Equitable Pediatric Clinical Use of AI.

The expanding role of artificial intelligence in the histopathological diagnosis in urological oncology: a literature review.

The ongoing growth of artificial intelligence (AI) involves virtually every aspect of oncologic care...

Development and external validation of a dynamic risk score for early prediction of cardiogenic shock in cardiac intensive care units using machine learning.

AIMS: Myocardial infarction and heart failure are major cardiovascular diseases that affect millions...

Classifying real-world macroscopic images in the primary-secondary care interface using transfer learning: implications for development of artificial intelligence solutions using nondermoscopic images.

BACKGROUND: The application of deep learning (DL) to diagnostic dermatology has been the subject of ...

Artificial Intelligence-Generated Social Media Content Creation and Management Strategies for Plastic Surgeons.

BACKGROUND: Social media platforms have come to represent integral components of the professional ma...

Automatic diagnosis of pediatric supracondylar humerus fractures using radiomics-based machine learning.

The aim of this study was to construct a classification model for the automatic diagnosis of pediatr...

Unraveling the complexity of the senescence-associated secretory phenotype in adamantinomatous craniopharyngioma using multimodal machine learning analysis.

BACKGROUND: Cellular senescence can have positive and negative effects on the body, including aiding...

Comparing Robot Controller Optimization Methods on Evolvable Morphologies.

In this paper, we compare Bayesian Optimization, Differential Evolution, and an Evolution Strategy e...

A Health Care Clinical Data Platform for Rapid Deployment of Artificial Intelligence and Machine Learning Algorithms for Cancer Care and Oncology Clinical Trials.

The xCures platform aggregates, organizes, structures, and normalizes clinical EMR data across care ...

A Compass for North Carolina Health Care Workers Navigating the Adoption of Artificial Intelligence.

This article underscores the economic benefits of AI, the importance of collaborative innovation, an...

[An overview of investments in the development of the Russian Medtech market and the prospects for the impact of digitalization in medicine on the economic performance of companies until 2030].

Today, the topic of digitalization, the introduction of innovations based on Big Data, the complexit...

Applications of Artificial Intelligence in Prostate Cancer Care: A Path to Enhanced Efficiency and Outcomes.

The landscape of prostate cancer care has rapidly evolved. We have transitioned from the use of conv...

Taming the chaos ?! - part 2: limitations of using eXplainable Artificial Intelligence (XAI) to tackle the complexity in psychotherapy of children and adolescents.

[New Technology, Warm Care: Social Robots in Nursing Practice and Research].

Recent, rapid advancements in technology have enabled the introduction and integration of robots int...

Predicting type 1 diabetes in children using electronic health records in primary care in the UK: development and validation of a machine-learning algorithm.

BACKGROUND: Children presenting to primary care with suspected type 1 diabetes should be referred im...

[Minimally invasive intelligent innovative technologies in foot and ankle surgery: development status and prospects].

The rapid development of technology has ushered in a new era of minimally invasive and intelligent s...

Artificial Intelligence and Ethical Frameworks in Pediatrics.

An interpretable predictive deep learning platform for pediatric metabolic diseases.

OBJECTIVES: Metabolic disease in children is increasing worldwide and predisposes a wide array of ch...

Omics-based deep learning approaches for lung cancer decision-making and therapeutics development.

Lung cancer has been the most common and the leading cause of cancer deaths globally. Besides clinic...