Pediatric radiology
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Pediatric radiology · Jun 2020
Letter Review Case ReportsComputed tomography of the lungs in novel corona virus (COVID-19) infection.
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Pediatric radiology · Apr 2019
ReviewMachine learning concepts, concerns and opportunities for a pediatric radiologist.
Machine learning, a subfield of artificial intelligence, is a rapidly evolving technology that offers great potential for expanding the quality and value of pediatric radiology. We describe specific types of learning, including supervised, unsupervised and semisupervised. Subsequently, we illustrate two core concepts for the reader: data partitioning and under/overfitting. ⋯ These include the requirement for very large data sets, the need to accurately label these images with a relatively small number of pediatric imagers, technical and regulatory hurdles, as well as the opaque character of convolution neural networks. We review machine learning cases in radiology including detection, classification and segmentation. Last, three pediatric radiologists from the Society for Pediatric Radiology Quality and Safety Committee share perspectives for potential areas of development.
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Pediatric radiology · Aug 2018
ReviewConsensus statement on abusive head trauma in infants and young children.
Abusive head trauma (AHT) is the leading cause of fatal head injuries in children younger than 2 years. A multidisciplinary team bases this diagnosis on history, physical examination, imaging and laboratory findings. Because the etiology of the injury is multifactorial (shaking, shaking and impact, impact, etc.) the current best and inclusive term is AHT. ⋯ There is no substantiation, at a time remote from birth, that an asymptomatic birth-related subdural hemorrhage can result in rebleeding and sudden collapse. Further, a diagnosis of AHT is a medical conclusion, not a legal determination of the intent of the perpetrator or a diagnosis of murder. We hope that this consensus document reduces confusion by recommending to judges and jurors the tools necessary to distinguish genuine evidence-based opinions of the relevant medical community from legal arguments or etiological speculations that are unwarranted by the clinical findings, medical evidence and evidence-based literature.
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In juvenile idiopathic arthritis (JIA), imaging is increasingly used in clinical practice. In this paper we discuss imaging of the knee, the clinically most commonly affected joint in JIA. ⋯ The validation processes of MRI as an imaging biomarker for clinical trials in the JIA knee are at an advanced stage, with important data available on the feasibility, reliability and validity of the Juvenile Arthritis MRI Scoring system. Moreover, both US and MRI data are emerging on the normal appearance of the growing knee joint.