, Ĭharniak E, Johnson M (2005) Coarse-to-fine n-best parsing and Ma圎nt discriminative reranking. O’Reilly Media, IncĬhapman WW, Bridewell W, Hanbury P, Cooper GF, Buchanan BG (2001) A simple algorithm for identifying negated findings and diseases in discharge summaries. In: ICCVīird S, Klein E, Loper E (2009) Natural language processing with Python. īa J, Swersky K, Fidler S, Salakhutdinov R (2015) Predicting deep zero-shot convolutional neural networks using textual descriptions. In: ICCVĪronson AR, Lang FM (2010) An overview of MetaMap: historical perspective and recent advances. Although the initial quantitative results are promising as reported, deep convolutional neural network-based “reading chest X-rays” (i.e., recognizing and locating the common disease patterns trained with only image-level labels) remains a strenuous task for fully automated high-precision CAD systems.Īntol S, Agrawal A, Lu J, Mitchell M, Batra D, Zitnick L (2015) Vqa: visual question answering. Importantly, we demonstrate that these commonly occurring thoracic diseases can be detected and even spatially located via a unified weakly supervised multi-label image classification and disease localization framework, which is validated using our proposed dataset. In this chapter, we present a chest X-ray database, namely, “ChestX-ray”, which comprises 121,120 frontal-view X-ray images of 30,805 unique patients with the text-mined eight disease image labels (where each image can have multi-labels), from the associated radiological reports using natural language processing. On the other side, it is still an open question how this type of hospital-size knowledge database containing invaluable imaging informatics (i.e., loosely labeled) can be used to facilitate the data-hungry deep learning paradigms in building truly large-scale high-precision computer-aided diagnosis (CAD) A tremendous number of X-ray imaging studies accompanied by radiological reports are accumulated and stored in many modern hospitals’ picture archiving and communication systems (PACS) The chest X-ray is one of the most commonly accessible radiological examinations for screening and diagnosis of many lung diseases.
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