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NLP Algorithms Endowed for Automatic Extraction of Information from Unstructured Free-Text Reports of Radiology Monarchy

2020 VOLUME-8 ISSUE-10, AUGUST 2019, REGULAR ISSUE  
Natural Language Processing (NLP) Algorithms are the key factors for automatic information extraction form the unstructured free-text radiology reports .To extract clinically important findings and recommendations  ...  Thus through this survey we can say that, NLP methods used to extract information ,brings new insights into already known clinical evidences.  ...  NLP Algorithms Endowed for Automatic Extraction of Information from Unstructured Free-Text Reports of Radiology Monarchy Sr.No.  ... 
doi:10.35940/ijitee.l8009.1091220 fatcat:sjth33dnvjfnhn442figt75llq

Unsupervised Topic Modeling in a Large Free Text Radiology Report Repository

Saeed Hassanpour, Curtis P. Langlotz
2015 Journal of digital imaging  
The free text format and the subtlety and variations of natural language hinder the extraction of reusable information from radiology reports for decision support, quality improvement, and biomedical research  ...  Most of this critical information is entered in free text format, even when structured radiology report templates are used.  ...  The majority of report information content, even in presence of structured templates, is captured in free text.  ... 
doi:10.1007/s10278-015-9823-3 pmid:26353748 pmcid:PMC4722022 fatcat:yh4tag7kyjfwhfjoucdduullxa

Text Mining in Radiology Reports

Tianxia Gong, Chew Lim Tan, Tze Yun Leong, Cheng Kiang Lee, Boon Chuan Pang, C. C. Tchoyoson Lim, Qi Tian, Suisheng Tang, Zhuo Zhang
2008 2008 Eighth IEEE International Conference on Data Mining  
In this paper, we propose a text mining system to extract and use the information in radiology reports.  ...  However, as most reports are in free text format, the valuable information contained in those reports cannot be easily accessed and used, unless proper text mining has been applied.  ...  Text assisted medical image feature extraction Like extracting information from free text, feature extraction from images are necessary for many image mining applications such as content based information  ... 
doi:10.1109/icdm.2008.150 dblp:conf/icdm/GongTLLPLTTZ08 fatcat:jkirthazjjasphtqsqnepvvjqy

A Natural Language Processing Pipeline of Chinese Free-text Radiology Reports for Liver Cancer Diagnosis [article]

Honglei Liu, Yan Xu, Zhiqiang Zhang, Ni Wang, Yanqun Huang, Zhenghan Yang, Rui Jiang, Hui Chen
2020 arXiv   pre-print
This study sought to design an NLP pipeline for the direct extraction of clinically relevant features from Chinese radiology reports, which is the first key step in computer-aided radiologic diagnosis.  ...  The features extracted by the NLP pipeline conformed to the original meaning of the radiology reports.  ...  the structured features instead of the free-text reports.  ... 
arXiv:2004.13848v1 fatcat:e6swxr2lprdqjocmdh27r2ytm4

Investigation of Terminology Coverage in Radiology Reporting Templates and Free-text Reports

Yi Hong, Jin Zhang
2015 International Journal of Knowledge Content Development and Technology  
To compare term occurrences in free-text radiology reports and RSNA reporting templates, the Wilcoxon signed-rank test method was applied to investigate how much of the content of conventional narrative  ...  The results show that the RSNA reporting templates cover most terms that appear in actual radiology reports.  ...  We thank the RSNA Radiology Informatics Committee for leading and supporting the radiology reporting initiative, and we acknowledge the many RSNA volunteers who helped develop the reporting templates.  ... 
doi:10.5865/ijkct.2015.5.1.005 fatcat:s7pgavmdlbbjtbzmb7nllassim

A Natural Language Processing Pipeline of Chinese Free-text Radiology Reports for Liver Cancer Diagnosis

Honglei Liu, Yan Xu, Zhiqiang Zhang, Ni Wang, Yanqun Huang, Yanjun Hu, Zhenghan Yang, Rui Jiang, Hui Chen
2020 IEEE Access  
NLP was performed to extract radiological features with terms from the radiology reports.  ...  Building a comprehensive NLP pipeline for information extraction from Chinese radiology reports has great importance for further NLP research.  ... 
doi:10.1109/access.2020.3020138 fatcat:jgfachrsqfgwxggkbuug4r27pe

BI-RADS BERT and Using Section Segmentation to Understand Radiology Reports

Grey Kuling, Belinda Curpen, Anne L. Martel
2022 Journal of Imaging  
This model achieved 98% accuracy in segregating free-text reports, sentence by sentence, into sections of information outlined in the Breast Imaging Reporting and Data System (BI-RADS) lexicon, which is  ...  Radiology reports are one of the main forms of communication between radiologists and other clinicians, and contain important information for patient care.  ...  Acknowledgments: We want to acknowledge Compute Canada for their computational resources from Simon Fraser University, B.C., Canada.  ... 
doi:10.3390/jimaging8050131 fatcat:kz64ch4l6vgtnk74as574tqvhe

Automating Quality Control for Structured Standardized Radiology Reports Using Text Analysis

Anjani Dhrangadhariya, Sandy Millius, Cyril Thouly, Benoit Rizk, Dominique Fournier, Henning Müller, Hugues Brat
2020 Studies in Health Technology and Informatics  
It notably maps the free text onto MeSH terms and checks if the anatomy and disease terms match in the indication and conclusion of a report.  ...  Radiology reports describe the findings of a radiologist in an imaging examination, produced for another clinician in order to answer to a clinical indication.  ...  Results Prototype developed The developed prototype fetches a non-empty, radiology report file from internal storage followed by rule-based extraction of free text from the indication and conclusion  ... 
doi:10.3233/shti200122 pmid:32570346 fatcat:poywo63xrfgdldr5sghcyy522m

Validation of Semantic Analyses of Unstructured Medical Data for Research Purposes
Validierung von semantischen Analysen von unstrukturierten medizinischen Daten für Forschungszwecke

Roman Michael Pokora, Lucian Le Cornet, Philipp Daumke, Peter Mildenberger, Hajo Zeeb, Maria Blettner
2019 Das Gesundheitswesen  
For automated tagging and reporting, the text analysis software Averbis Extraction Platform (AEP) was used.  ...  Background In secondary data there are often unstructured free texts. The aim of this study was to validate a text mining system to extract unstructured medical data for research purposes.  ...  The AEP was not provided free of Charge, however the second human classification was provided free of Charge.  ... 
doi:10.1055/a-1007-8540 pmid:31597185 fatcat:6bjengcyknhs7jli5zirjqavxe

BI-RADS BERT Using Section Segmentation to Understand Radiology Reports [article]

Grey Kuling, Dr. Belinda Curpen, Anne L. Martel
2022 arXiv   pre-print
This model achieved a 98% accuracy at segregating free text reports sentence by sentence into sections of information outlined in the Breast Imaging Reporting and Data System (BI-RADS) lexicon, a significant  ...  Radiology reports are one of the main forms of communication between radiologists and other clinicians and contain important information for patient care.  ...  the information from the whole free text report.  ... 
arXiv:2110.07552v2 fatcat:knhasjoudzconjigxqx6mwgb7m

Assisting Radiologists with Reporting Urgent Findings to Referring Physicians: A Machine Learning Approach to Identify Cases for Prompt Communication

Xing Meng, Craig H. Ganoe, Ryan T. Sieberg, Yvonne Y. Cheung, Saeed Hassanpour
2019 Journal of Biomedical Informatics  
To test our approach, we created a corpus of 480 radiology reports from our own institution and double-annotated cases that required prompt communication by two radiologists.  ...  This semi-supervised learning approach requires a minimal amount of manual annotations and was trained on a large multi-institutional radiology report repository from three major external healthcare organizations  ...  Finally, a supervised text classification system was developed to annotate and extract clinically significant information from free-text radiology reports [16] .  ... 
doi:10.1016/j.jbi.2019.103169 pmid:30959206 pmcid:PMC6506378 fatcat:a54c3pvit5aivmq6rxmsdq6vum

Automatic extraction of PIOPED interpretations from ventilation/perfusion lung scan reports

M Fiszman, P J Haug, P R Frederick
1998 Proceedings. AMIA Symposium  
Free-text documents are the main type of data produced by a radiology department in a hospital information system.  ...  We have used a natural language processing tool called SymText to extract relevant clinical information from a different type of radiology report, the Ventilation/Perfusion lung scan report.  ...  Acknowledgments Supported in part by Grant #LM06539 from the National Library of Medicine and Grant #HL53427 from the National Heart, Lung & Blood Institute. Dr.  ... 
pmid:9929341 pmcid:PMC2232386 fatcat:ddievkcnqzdztctmdvp5fi444u

Text Mining in Radiology Reports by SVM Classifier

Anuradha K.Bodile, Manali Kshirsagar
2015 International Journal of Computer Applications  
In Radiology research area, most of the reports are in free text format and usually unprocessed, hence it is difficult to access the valuable information for medical professional unless proper text mining  ...  There are some systems for radiology report information retrieval like MedLEE, NeuRadIR, CBIR but very few of them make use of text associated with image This paper proposes a text mining system to deals  ...  A text mining system [1] extracts and uses information from reports.  ... 
doi:10.5120/20212-2476 fatcat:pbgr3yr6cbdsvkiurahr5uudjm

An artificial intelligence natural language processing pipeline for information extraction in neuroradiology [article]

Henry Watkins, Robert Gray, Ashwani Jha, Parashkev Nachev
2021 arXiv   pre-print
In this work we present a natural language processing pipeline for information extraction of radiological reports in neurology.  ...  We show our pipeline, called 'neuroNLP', can reliably extract clinically relevant information from these reports, enabling downstream modelling of reports and associated imaging on a heretofore unprecedented  ...  Methods Pipeline The purpose of this work is to create a deep learning informed pipeline to clean and extract clinically relevant information from the free text of neuroradiological reports.  ... 
arXiv:2107.10021v1 fatcat:czyujlwkvnaejltvpcigxu5p2m

T-staging pulmonary oncology from radiological reports using natural language processing: translating into a multi-language setting

J. Martijn Nobel, Sander Puts, Jakob Weiss, Hugo J. W. L. Aerts, Raymond H. Mak, Simon G. F. Robben, André L. A. J. Dekker
2021 Insights into Imaging  
Conclusions NLP can be successfully applied for staging lung cancer from free-text radiological reports in different languages.  ...  To support data extraction from free-text radiological reports, Dutch natural language processing (NLP) algorithm was built to quantify T-stage of pulmonary tumors according to the tumor node metastasis  ...  Next to extracting tumor endpoints and follow-up from radiological reports, NLP algorithms can also be used to extract tumor staging from free text.  ... 
doi:10.1186/s13244-021-01018-1 pmid:34114076 fatcat:zigrtbpf4vgflmgwtgaerrwk7e
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