Latest AI and machine learning research in pediatrics for healthcare professionals.
An individualized innovative disease management is of great importance for people with multiple sclerosis (pwMS) to cope with the complexity of this chronic, multidimensional disease. However, an individual state of the art strategy, with precise adjustment to the patient's characteristics, is still far from being part of the everyday care of pwMS. The development of digital twins could decisively...
Modeling of hemodynamics and artificial intelligence have great potential to support clinical diagnosis and decision making. While hemodynamics modeling is extremely time- and resource-consuming, machine learning (ML) typically requires large training data that are often unavailable. The aim of this study was to develop and evaluate a novel methodology generating a large database of synthetic case...
Clinical oncology is experiencing rapid growth in data that are collected to enhance cancer care. With recent advances in the field of artificial inte...
OBJECTIVE: Risk assessment tools typically used in congenital heart surgery (CHS) assume that various possible risk factors interact in a linear and a...
The heart murmur associated with atrial septal defects is often faint and can thus only be detected by chance. Although electrocardiogram examination ...
This study presents the kinetics of production of a glycolipopeptide biosurfactant in a medium previously co-optimized by response surface and neural ...
In sub-Saharan Africa, there is a significant unmet need for emergency care, with a shortage of trained providers. One model to increase the number of...
OBJECTIVE: To create a personalised machine learning model for prediction of severe adverse neonatal outcomes (SANO) during the second stage of labour...
BACKGROUND: Streptococcus pyogenes is a leading cause of infection-related morbidity and mortality. A reinvigorated vaccine development effort calls f...
COVID-19, a viral infection originated from Wuhan, China has spread across the world and it has currently affected over 115 million people. Although v...
Emerging manifestations of artificial intelligence (AI) have featured prominently in virtually all industries and facets of our lives. Within the radi...
Artificial intelligence (AI) uses computers to mimic cognitive functions of the human brain, allowing inferences to be made from generally large datas...
Drug designing and development is an important area of research for pharmaceutical companies and chemical scientists. However, low efficacy, off-targe...
Respiratory diseases, including asthma, bronchitis, pneumonia, and upper respiratory tract infection (RTI), are among the most common diseases in clin...
PURPOSE: We aimed to introduce an explainable machine learning technology to help clinicians understand the risk factors for neonatal postoperative mo...
This paper sketches a new approach using Fuzzy Cognitive Maps (FCMs) to operably map and simulate digital transformation in architecture and urban pla...
The purposes are to monitor the nitrogen utilization efficiency of crops and intelligently evaluate the absorption of nutrients by crops during the pr...
INTRODUCTION: Sudden unexpected death in infancy (SUDI) represents the commonest presentation of postneonatal death. We explored whether machine learn...
INTRODUCTION: Pediatric surgery began with single-incision flank surgery and has evolved to multi-port laparoscopic and robotic approaches. Recent tec...
No data exist concerning the appication of a new robotic system with 3 mm instruments (Senhance®, Transenterix) in infants and small children. Therefo...