About: Deep learning in generating radiology reports: A survey

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An Entity of Type : schema:ScholarlyArticle, within Data Space : covidontheweb.inria.fr associated with source document(s)

Attributes	Values
type	Academic Article research paper schema:ScholarlyArticle
isDefinedBy	Covid-on-the-Web dataset
has title	Deep learning in generating radiology reports: A survey
Creator	Chung, Chung, Vera Poon, Josiah Maram, Mahmoud Monshi, Monshi, Josiah Poon, Vera
Source	Elsevier; Medline; PMC
abstract	Substantial progress has been made towards implementing automated radiology reporting models based on deep learning (DL). This is due to the introduction of large medical text/image datasets. Generating radiology coherent paragraphs that do more than traditional medical image annotation, or single sentence-based description, has been the subject of recent academic attention. This presents a more practical and challenging application and moves towards bridging visual medical features and radiologist text. So far, the most common approach has been to utilize publicly available datasets and develop DL models that integrate convolutional neural networks (CNN) for image analysis alongside recurrent neural networks (RNN) for natural language processing (NLP) and natural language generation (NLG). This is an area of research that we anticipate will grow in the near future. We focus our investigation on the following critical challenges: understanding radiology text/image structures and datasets, applying DL algorithms (mainly CNN and RNN), generating radiology text, and improving existing DL based models and evaluation metrics. Lastly, we include a critical discussion and future research recommendations. This survey will be useful for researchers interested in DL, particularly those interested in applying DL to radiology reporting.
has issue date	2020-05-15(xsd:dateTime)
bibo:doi	10.1016/j.artmed.2020.101878
bibo:pmid	32425358
has license	no-cc
sha1sum (hex)	362506fe8e0a20fd60fe6b657004d1fd9e549cef
schema:url	https://doi.org/10.1016/j.artmed.2020.101878
resource representing a document's title	Deep learning in generating radiology reports: A survey
has PubMed Central identifier	PMC7227610
has PubMed identifier	32425358
schema:publication	Artif Intell Med
resource representing a document's body	covid:362506fe8e0a20fd60fe6b657004d1fd9e549cef#body_text
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