Pediatrics

Using Social Media to Understand Primary Discussions in Gastrointestinal Cancers: Machine Learning Approach.

BACKGROUND: The incidence and mortality rates of gastrointestinal (GI) cancers are high in the United States as well as worldwide. The widespread use of social media provides unique opportunities to facilitate the dissemination of information, especially in the context of health. OBJECTIVE: We aim to characterize the public's primary discussions, including perceptions, concerns, and interests towa...

Integrating Artificial Intelligence Into the Visualization and Modeling of Three-Dimensional Anatomy in Pediatric Surgical Patients.

BACKGROUND: Pediatric surgeons often treat patients with complex anatomical considerations due to congenital anomalies or distortion of normal structures by solid organ tumors. There are multiple applications for three-dimensional visualization of these structures based on cross-sectional imaging. Recently, advances in artificial intelligence (AI) applications and graphics hardware have made rapid...

Treatment with robot-assisted gait trainer Walkbot along with physiotherapy vs. isolated physiotherapy in children and adolescents with cerebral palsy. Experimental study.

BACKGROUND: Improving walking ability is a key objective in the treatment of children and adolescents with cerebral palsy, since it directly affects t...

The synergy of artificial intelligence and personalized medicine for the enhanced diagnosis, treatment, and prevention of disease.

INTRODUCTION: The completion of the Human Genome Project in 2003 marked the beginning of a transformative era in medicine. This milestone laid the fou...

Explainable Deep-Learning-Based Gait Analysis of Hip-Knee Cyclogram for the Prediction of Adolescent Idiopathic Scoliosis Progression.

Accurate prediction of scoliotic curve progression is crucial for guiding treatment decisions in adolescent idiopathic scoliosis (AIS). Traditional me...

YOLO-V5 based deep learning approach for tooth detection and segmentation on pediatric panoramic radiographs in mixed dentition.

OBJECTIVES: In the interpretation of panoramic radiographs (PRs), the identification and numbering of teeth is an important part of the correct diagno...

HAPI: An efficient Hybrid Feature Engineering-based Approach for Propaganda Identification in social media.

Social media platforms serve as communication tools where users freely share information regardless of its accuracy. Propaganda on these platforms ref...

Molecular docking aided machine learning for the identification of potential VEGFR inhibitors against renal cell carcinoma.

Renal cell carcinoma is a highly vascular tumor associated with vascular endothelial growth factor (VEGF) expression. The Vascular Endothelial Growth ...

Analyzing intelligent tourism development and public services based on a fuzzy genetic hybrid system to promote environmental and cultural values.

Environmental, cultural, and public service-dependent factors encourage the development of a country's tourism. In recent years, automated tourism dev...

Generative Pre-trained Transformer for Pediatric Stroke Research: A Pilot Study.

BACKGROUND: Pediatric stroke is an important cause of morbidity in children. Although research can be challenging, large amounts of data have been cap...

Applications of machine learning to MR imaging of pediatric low-grade gliomas.

INTRODUCTION: Machine learning (ML) shows promise for the automation of routine tasks related to the treatment of pediatric low-grade gliomas (pLGG) s...

Combining Federated Machine Learning and Qualitative Methods to Investigate Novel Pediatric Asthma Subtypes: Protocol for a Mixed Methods Study.

BACKGROUND: Pediatric asthma is a heterogeneous disease; however, current characterizations of its subtypes are limited. Machine learning (ML) methods...

Predicting negative attitudes towards suicide in social media texts: prediction model development and validation study.

BACKGROUND: Implementing machine learning prediction of negative attitudes towards suicide may improve health outcomes. However, in previous studies, ...

Developing an Effective Off-the-job Training Model and an Automated Evaluation System for Thoracoscopic Esophageal Atresia Surgery.

BACKGROUND: Pediatric minimally invasive surgery requires advanced technical skills. Off-the-job training (OJT), especially when using disease-specifi...

Artificial intelligence detects awareness of functional relation with the environment in 3 month old babies.

A recent experiment probed how purposeful action emerges in early life by manipulating infants' functional connection to an object in the environment ...

Evaluation of 3D T1-weighted spoiled gradient echo MR image quality using artificial intelligence image reconstruction techniques in the pediatric brain.

PURPOSE: To assess image quality and diagnostic confidence of 3D T1-weighted spoiled gradient echo (SPGR) MRI using artificial intelligence (AI) recon...

Artificial intelligence chatbots: Are they a reliable source for patients and families in pediatric neuro-oncology?

Automatic semantic segmentation of EHG recordings by deep learning: An approach to a screening tool for use in clinical practice.

BACKGROUND AND OBJECTIVE: Preterm delivery is an important factor in the disease burden of the newborn and infants worldwide. Electrohysterography (EH...

PND-Net: plant nutrition deficiency and disease classification using graph convolutional network.

Crop yield production could be enhanced for agricultural growth if various plant nutrition deficiencies, and diseases are identified and detected at e...

Concepts for the Development of Person-Centered, Digitally Enabled, Artificial Intelligence-Assisted ARIA Care Pathways (ARIA 2024).

The traditional healthcare model is focused on diseases (medicine and natural science) and does not acknowledge patients' resources and abilities to b...