Hasil Pencarian  ::  Simpan CSV :: Kembali

"The chest X-ray (CXR) or chest radiograph remains the most commonly ordered imaging study in medicine, yet paradoxically is often the most complex to learn, recall, and master effective and accurate interpretation. The chest radiograph includes all thoracic anatomy and provides a high yield, given the low cost and single source. This guide presents a structured lexicon for use by readers to reproducibly describe radiographic abnormalities of the chest detected on plain film CXRs. The lexicon is designed to provide readers with clinically significant differentiation of abnormalities detected. The content is structured to relate specific combinations of distinct radiographic findings to classes/groupings of pathological etiologies of those findings. Recognizing the individual findings and identifying their combination or lack of combination with other individual findings allows readers to create effective differential diagnoses that can then be further evaluated using other imaging procedures and/or non-radiographic clinical information. The book includes hundreds of images, including radiographs, CTs, graphics, and analogous models to help teach otherwise complex processes and radiographic principles."

"The emerging field of network science represents a new style of research that can unify such traditionally-diverse fields as sociology, economics, physics, biology, and computer science. It is a powerful tool in analyzing both natural and man-made systems, using the relationships between players within these networks and between the networks themselves to gain insight into the nature of each field. Until now, studies in network science have been focused on particular relationships that require varied and sometimes-incompatible datasets, which has kept it from being a truly universal discipline.Computational network science seeks to unify the methods used to analyze these diverse fields. This book provides an introduction to the field of Network Science and provides the groundwork for a computational, algorithm-based approach to network and system analysis in a new and important way. This new approach would remove the need for tedious human-based analysis of different datasets and help researchers spend more time on the qualitative aspects of network science research."