Latest AI and machine learning research in pediatrics for healthcare professionals.
BACKGROUND: Predicting infliximab pharmacokinetics (PK) is essential for optimizing individualized dosing in pediatric patients with Crohn disease (CD). Machine learning (ML) has emerged as a tool for predicting drug exposure; however, its development typically requires large datasets. This study aimed to develop an ML model for infliximab PK prediction by leveraging population PK model-based synt...
Addressing the challenge of achieving a global circular bioeconomy requires efficient and robust bio-based processes operating at different scales. These processes should also be competitive replacements for the production of chemicals currently obtained from fossil resources, as well as for the production of new-to-nature compounds. To that end, genetic circuits can be used to control cellular be...
BACKGROUND: The thalamus plays a crucial role in sensory processing, emotional regulation, and cognitive functions, and its dysregulation may be impli...
Trustworthiness has become a key concept for the ethical development and application of artificial intelligence (AI) in medicine. Various guidelines h...
BACKGROUND: Kawasaki disease (KD), a pediatric systemic vasculitis, lacks reliable diagnostic biomarkers and exhibits immune heterogeneity, complicati...
Artificial intelligence (AI) models have shown promise in predicting malignant thyroid nodules in adults; however, research on deep learning (DL) for...
BACKGROUND: Accurate bone age assessment is essential for determining the actual degree of development and indicating a disorder in growth. While clin...
Many studies have identified specific visual advantages in deaf individuals. However, few studies have linked these advantages to motor learning. This...
BACKGROUND: Early childhood caries (ECC) is a widespread pediatric dental condition that is influenced by a combination of biological, behavioral, and...
Monitoring cognitive development in early childhood enables detection of problems for timely intervention. However, currently recommended methods requ...
Artificial intelligence (AI) and deep learning are increasingly applied in cardiovascular imaging. However, the "black box" nature of these models ra...
This study investigates the application of machine learning (ML) techniques in diagnosing speech sound disorders (SSDs) in Saudi Arabic-speaking chil...
Chronic kidney disease (CKD) patients with coronavirus disease 2019 (COVID-19) are at significant risk of death. However, clinical identification of ...
UNLABELLED: Millions of people worldwide have diabetes, a disease that is becoming more common and has substantial socioeconomic costs. Artificial int...
This study investigates public sentiment toward COVID-19 vaccinations by analyzing Twitter data using advanced machine learning (ML) and natural langu...
BACKGROUND: Rice is one of the major food crops in the world, and the monitoring of its growth condition is of great significance for guaranteeing foo...
Generative artificial intelligence (AI), including large language models (LLMs), is rapidly transforming health care delivery, yet medical education r...
Persistent geographic and specialty-based disparities in health care workforce distribution have created critical gaps in rural health care access, re...
This study focuses on the binary classification of pediatric epilepsy seizure types as focal or generalized using Turkish electroencephalography (EEG)...
Artificial intelligence (AI) is rapidly transforming pediatric oncology by creating new means to improve the accuracy and efficacy of cancer diagnosis...