Artificial intelligence in paediatric radiology: future opportunities
N Davendralingam, NJ Sebire… - The British Journal of …, 2021 - academic.oup.com
Artificial intelligence (AI) has received widespread and growing interest in healthcare, as a
method to save time, cost and improve efficiencies. The high-performance statistics and …
method to save time, cost and improve efficiencies. The high-performance statistics and …
Transforming neonatal care with artificial intelligence: challenges, ethical consideration, and opportunities
Artificial intelligence (AI) offers tremendous potential to transform neonatology through
improved diagnostics, personalized treatments, and earlier prevention of complications …
improved diagnostics, personalized treatments, and earlier prevention of complications …
Artificial intelligence outcome prediction in neonates with encephalopathy (AI-OPiNE)
Purpose To develop a deep learning algorithm to predict 2-year neurodevelopmental
outcomes in neonates with hypoxic-ischemic encephalopathy using MRI and basic clinical …
outcomes in neonates with hypoxic-ischemic encephalopathy using MRI and basic clinical …
Multi-channel attention-fusion neural network for brain age estimation: Accuracy, generality, and interpretation with 16,705 healthy MRIs across lifespan
Brain age estimated by machine learning from T1-weighted magnetic resonance images
(T1w MRIs) can reveal how brain disorders alter brain aging and can help in the early …
(T1w MRIs) can reveal how brain disorders alter brain aging and can help in the early …
The role of MRI-based texture analysis to predict the severity of brain injury in neonates with perinatal asphyxia
FC Sarioglu, O Sarioglu, H Guleryuz… - The British Journal of …, 2022 - academic.oup.com
Objective: To evaluate the efficacy of the MRI-based texture analysis (TA) of the basal
ganglia and thalami to distinguish moderate-to-severe hypoxic-ischemic encephalopathy …
ganglia and thalami to distinguish moderate-to-severe hypoxic-ischemic encephalopathy …
BOston Neonatal Brain Injury Data for Hypoxic Ischemic Encephalopathy (BONBID-HIE): I. MRI and Lesion Labeling
Hypoxic ischemic encephalopathy (HIE) is a brain injury that occurs in 1~ 5/1000 term
neonates. Accurate identification and segmentation of HIE-related lesions in neonatal brain …
neonates. Accurate identification and segmentation of HIE-related lesions in neonatal brain …
Machine-learning based prediction of future outcome using multimodal MRI during early childhood
The human brain undergoes rapid changes from the fetal stage to two years postnatally,
during which proper structural and functional maturation lays the foundation for later …
during which proper structural and functional maturation lays the foundation for later …
Study protocol: retrospectively mining multisite clinical data to presymptomatically predict seizure onset for individual patients with Sturge-Weber
Introduction Secondary analysis of hospital-hosted clinical data can save time and cost
compared with prospective clinical trials for neuroimaging biomarker development. We …
compared with prospective clinical trials for neuroimaging biomarker development. We …
Current perspectives of artificial intelligence in pediatric neuroradiology: an overview
D Martin, E Tong, B Kelly, K Yeom, V Yedavalli - Frontiers in radiology, 2021 - frontiersin.org
Artificial Intelligence, Machine Learning, and myriad related techniques are becoming ever
more commonplace throughout industry and society, and radiology is by no means an …
more commonplace throughout industry and society, and radiology is by no means an …
Learning the impact of acute and chronic diseases on forecasting neonatal encephalopathy
Objective There is a wide range of risk factors predisposing to the onset of neonatal
encephalopathy (NE), including maternal antepartum/intrapartum comorbidities or events …
encephalopathy (NE), including maternal antepartum/intrapartum comorbidities or events …