Pediatrics

Urban change detection: assessing biophysical drivers using machine learning and Google Earth Engine.

Urban areas are experiencing rapid transformations, driven by population growth, economic development, and policy changes. Understanding and monitoring these dynamic changes is crucial for sustainable urban planning and management. This study leverages machine learning and Google Earth Engine to investigate urban dynamics and its interactions with biophysical conditions in the Kaduna River Basin (...

Evaluating the change and trend of construction land in Changsha City based GeoSOS-FLUS model and machine learning methods.

This study systematically analyzes the land use changes in Changsha City from 2000 to 2023. Three classification models-Random Forest (RF), Gradient Boosting Decision Tree (GBDT), and Artificial Neural Network (ANN) were employed to evaluate the accuracy of land use classification. The RF model, with an accuracy of 95.78%, outperformed the others, demonstrating its robustness and generalization ab...

Artificial intelligence impacts in education and pediatric mental health.

PURPOSE OF REVIEW: Increased accessibility of artificial intelligence to children has raised concerns regarding its effects on education and student m...

Predicting low birth weight risks in pregnant women in Brazil using machine learning algorithms: data from the Araraquara cohort study.

BACKGROUND: Low birth weight (LBW) is a critical factor linked to neonatal morbidity and mortality. Early prediction is essential for timely intervent...

Large Language Models for Pediatric Differential Diagnoses in Rural Health Care: Multicenter Retrospective Cohort Study Comparing GPT-3 With Pediatrician Performance.

BACKGROUND: Rural health care providers face unique challenges such as limited specialist access and high patient volumes, making accurate diagnostic ...

User-Centered Prototype Design of a Health Care Robot for Treating Type 2 Diabetes in the Community Pharmacy: Development and Usability Study.

BACKGROUND: Technology can be an effective tool for providing health services and disease self-management, especially in diabetes care. Technology too...

Chinese Medicine in the Era of Artificial Intelligence: Challenges and Development Prospects.

Traditional Chinese medicine (TCM) has protected the health of Chinese people for thousands of years. With the rapid development of artificial intelli...

Automation of protein crystallization scaleup via Opentrons-2 liquid handling.

In this study we present an approach for optimizing protein crystallization trials at the multi-microliter scale utilizing the Opentrons-2 liquid hand...

Re-imagining human cell culture media: Challenges, innovations, and future directions.

The development of optimized culture media is pivotal to advancements in human cell culture, underpinning progress in regenerative medicine, cell ther...

Hydroxyl Dicarboxylic Acids at a Mountainous Site in Hong Kong: Formation Mechanisms and Implications for Particle Growth.

Secondary organic aerosol (SOA) has been shown to significantly impact climate, air quality, and human health. Hydroxyl dicarboxylic acids (OHDCA) are...

Deep learning algorithm classification of tympanostomy tube images from a heterogenous pediatric population.

IMPORTANCE: The ability to augment routine post-operative tube check appointments with at-home digital otoscopes and deep learning AI could improve he...

Predicting infant brain connectivity with federated multi-trajectory GNNs using scarce data.

The understanding of the convoluted evolution of infant brain networks during the first postnatal year is pivotal for identifying the dynamics of earl...

Three-dimensional markerless surface topography approach with convolutional neural networks for adolescent idiopathic scoliosis screening.

Adolescent idiopathic scoliosis (AIS) is a three-dimensional lateral and torsional deformity of the spine, affecting up to 5% of the population. Tradi...

Do Treatment Choices by Artificial Intelligence Correspond to Reality? Retrospective Comparative Research with Necrotizing Enterocolitis as a Use Case.

BackgroundIn cases of surgical necrotizing enterocolitis (NEC), the choice between laparotomy (LAP) or comfort care (CC) presents a complex, ethical d...

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 obligatory use of digital media in many sectors, as is t...

Modifiable risk factors of vaccine hesitancy: insights from a mixed methods multiple population study combining machine learning and thematic analysis during the COVID-19 pandemic.

BACKGROUND: Vaccine hesitancy, the delay in acceptance or reluctance to vaccinate, ranks among the top threats to global health. Identifying modifiabl...

A machine learning approach to predict mortality and neonatal persistent pulmonary hypertension in newborns with congenital diaphragmatic hernia. A retrospective observational cohort study.

UNLABELLED: Congenital diaphragmatic hernia (CDH) has high morbidity and mortality rates. This study aimed to develop a machine learning (ML) algorith...

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 silico identification of tumor neoantigens (TNAs) ...

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 predict hypertension in children and adolescents ac...

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 healthcare, with AI being touted as a solution for ...