Pediatrics

Made in China 2025: Artificial intelligence intervention and urban green economy development.

Against the backdrop of the profound adjustment of the global industrial structure and the rise of the Fourth Industrial Revolution, the contradiction between rapid economic growth and ecological environmental protection has become increasingly prominent. Promoting green development has become a key path to achieving sustainable urban development. In 2015, China launched the "Made in China (2025)″...

Exploring advanced deep learning approaches in cardiac image analysis: A comprehensive review.

BACKGROUND: Cardiac image analysis plays an important role in detecting and categorizing cardiovascular diseases (CVDs), such as coronary artery disease (CAD), heart failure, congenital heart defects, arrhythmias (irregular heartbeat), and valvular heart disease. The automated identification of these diseases represents a significant advancement in achieving early diagnosis and mitigating disease ...

Artificial intelligence and regional anesthesiology education curriculum development: navigating the digital noise.

Artificial intelligence (AI) has demonstrated a disruptive ability to enhance and transform clinical medicine. While the dexterous nature of anesthesi...

Predictive analysis of pediatric gastroenteritis risk factors and seasonal variations using VGG Dense HybridNetClassifier a novel deep learning approach.

Pediatric gastroenteritis is a major reason for sickness and death among children worldwide, especially in places where healthcare and clean sanitatio...

How does artificial intelligence accelerate the energy transition? Learning from empirical experience in OECD countries.

The need for an energy transition is increasing due to technological advancements and rapid economic growth, especially in developed countries. As a r...

Deep learning-driven insights into the transmission dynamics of hepatitis B virus with treatment.

Viral infections have spread globally, profoundly affecting social and economic aspects of life and causing widespread suffering. Infection caused by ...

Dose-Dependent Effects of Butachlor Accumulation and Degradation on Amino Acid Metabolism and Lignin Biosynthesis in Rice.

The excessive use of amide herbicides (AHs) poses a substantial environmental threat by disrupting the growth and development of crops. Using butachlo...

Health consumers' use and perceptions of health information from generative artificial intelligence chatbots: A scoping review.

Background Health consumers can use generative artificial intelligence (GenAI) chatbots to seek health information. As GenAI chatbots continue to impr...

Dual smart sensor data-based deep learning network for premature infant hypoglycemia detection.

In general, deficient birth weight neonates suffer from hypoglycemia, and this can be quite disadvantageous. Like oxygen, glucose is a building block ...

Listening deeper: neural networks unravel acoustic features in preterm infant crying.

Early infant crying provides critical insights into neurodevelopment, with atypical acoustic features linked to conditions such as preterm birth. Howe...

WeedSwin hierarchical vision transformer with SAM-2 for multi-stage weed detection and classification.

Weed detection and classification using computer vision and deep learning techniques have emerged as crucial tools for precision agriculture, offering...

GAINSeq: glaucoma pre-symptomatic detection using machine learning models driven by next-generation sequencing data.

Congenital glaucoma, a complex and diverse condition, presents considerable difficulties in its identification and categorization. This research used ...

Deep learning strategies for semantic segmentation of pediatric brain tumors in multiparametric MRI.

Automated segmentation of pediatric brain tumors (PBTs) can support precise diagnosis and treatment monitoring, but it is still poorly investigated in...

Enhancing sarcasm detection in sentiment analysis for cyberspace safety using advanced deep learning techniques.

Social media has become an integral part of daily life, with platforms like Twitter serving as popular outlets for users to share information and expr...

Harnessing AI for Improved Diagnosis and Management of Pediatric Sepsis: Current Advances, Challenges, and Future Directions.

Artificial intelligence (AI) has been applied to early recognition and management of rapidly progressive, community-acquired pediatric sepsis, a leadi...

ARTIFICIAL INTELLIGENCE ENHANCES DIAGNOSTIC ACCURACY OF CONTRAST ENEMAS IN HIRSCHSPRUNG DISEASE COMPARED TO CLINICAL EXPERTS.

Introduction Contrast enema (CE) is widely used in the evaluation of suspected Hirschsprung disease (HD). Deep learning is a promising tool to standar...

Lessons learned from RadiologyNET foundation models for transfer learning in medical radiology.

Deep learning models require large amounts of annotated data, which are hard to obtain in the medical field, as the annotation process is laborious an...

Aggressiveness-guided nodule management for lung cancer screening in Europe-justification for follow-up intervals and definition of growth.

The European Society of Thoracic Imaging (ESTI) nodule management recommendation for lung cancer screening with low-dose CT builds on existing nodule ...

Artificial neural network-driven approaches to improved forecasting of disability care expenditures in an aging Kingdom of Saudi Arabia population.

The total number of older persons globally (those aged 60 years and above) was 202 million in 1950; this total multiplied to attain 901 million and is...

Potential use of saliva infrared spectra and machine learning for a minimally invasive screening test for congenital syphilis in infants.

Congenital syphilis is a global public health issue, and its diagnostic complexity poses a challenge to early treatment. Fourier Transform Infrared Sp...