Pediatrics

Deep learning-based automated bone age estimation for Saudi patients on hand radiograph images: a retrospective study.

PURPOSE: In pediatric medicine, precise estimation of bone age is essential for skeletal maturity ev...

Application of ChatGPT in pediatric surgery and further issues that should be addressed: comment.

[Use of artificial intelligence in geographic atrophy in age-related macular degeneration].

The first regulatory approval of treatment for geographic atrophy (GA) secondary to age-related macu...

Accuracy and transportability of machine learning models for adolescent suicide prediction with longitudinal clinical records.

Machine Learning models trained from real-world data have demonstrated promise in predicting suicide...

Making Co-Design More Responsible: Case Study on the Development of an AI-Based Decision Support System in Dementia Care.

BACKGROUND: Emerging technologies such as artificial intelligence (AI) require an early-stage assess...

Evaluation of Comfort Behavior Levels of Newborn by Artificial Intelligence Techniques.

BACKGROUND: One of the scales most frequently used in the evaluation of newborn comfort levels is th...

Identification of severe acute pediatric asthma phenotypes using unsupervised machine learning.

RATIONALE: More targeted management of severe acute pediatric asthma could improve clinical outcomes...

Artificial intelligence assisted diagnosis of chronic lymphocytic leukemia in a historic pediatric case using large language models.

A machine learning approach to predict in vivo skin growth.

Since their invention, tissue expanders, which are designed to trigger additional skin growth, have ...

An attention-based deep learning for acute lymphoblastic leukemia classification.

The bone marrow overproduces immature cells in the malignancy known as Acute Lymphoblastic Leukemia ...

Diagnostic Performance of Machine Learning-based Models in Neonatal Sepsis: A Systematic Review.

BACKGROUND: Timely diagnosis of neonatal sepsis is challenging. We aimed to systematically evaluate ...

Testing behaviour change with an artificial intelligence chatbot in a randomized controlled study.

Chatbots can effect large-scale behaviour change because they are accessible through social media, f...

AGILE platform: a deep learning powered approach to accelerate LNP development for mRNA delivery.

Ionizable lipid nanoparticles (LNPs) are seeing widespread use in mRNA delivery, notably in SARS-CoV...

Unlocking Tomorrow's Health Care: Expanding the Clinical Scope of Wearables by Applying Artificial Intelligence.

As an integral aspect of health care, digital technology has enabled modelling of complex relationsh...

Biomedical Data Science, Artificial Intelligence, and Ethics: Navigating Challenges in the Face of Explosive Growth.

Advances in biomedical data science and artificial intelligence (AI) are profoundly changing the lan...

Healthcare leaders' experiences of implementing artificial intelligence for medical history-taking and triage in Swedish primary care: an interview study.

BACKGROUND: Artificial intelligence (AI) holds significant promise for enhancing the efficiency and ...

Green finance growth prediction model based on time-series conditional generative adversarial networks.

Climate change mitigation necessitates increased investment in green sectors. This study proposes a ...

Machine learning-enhanced HRCT analysis for diagnosis and severity assessment in pediatric asthma.

OBJECTIVES: Chest high-resolution computed tomography (HRCT) is conditionally recommended to rule ou...

Amino acid metabolomics and machine learning-driven assessment of future liver remnant growth after hepatectomy in livers of various backgrounds.

Accurate assessment of future liver remnant growth after partial hepatectomy (PH) in patients with d...

From Web to RheumaLpack: Creating a Linguistic Corpus for Exploitation and Knowledge Discovery in Rheumatology.

This study introduces RheumaLinguisticpack (RheumaLpack), the first specialised linguistic web corpu...

Deep learning classification of pediatric spinal radiographs for use in large scale imaging registries.

PURPOSE: The purpose of this study is to develop and apply an algorithm that automatically classifie...