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CheXbert: Combining Automatic Labelers and Expert Annotations for Accurate Radiology Report Labeling Using BERT
[article]
2020
arXiv
pre-print
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In this work, we introduce a BERT-based approach to medical image report labeling that exploits both the scale of available rule-based systems and the quality of expert annotations. ...
We demonstrate superior performance of a biomedically pretrained BERT model first trained on annotations of a rule-based labeler and then finetuned on a small set of expert annotations augmented with automated ...
Thanks to Alistair Johnson for support in the radiologist benchmark, to Jeremy Irvin for support in the CheXpert labeler, Alex Tamkin for helpful comments, and Yifan Peng for helpful feedback. ...
arXiv:2004.09167v3
fatcat:ibixaghabnakljrfyw2c7azs6y
Combining Automatic Labelers and Expert Annotations for Accurate Radiology Report Labeling Using BERT
2020
Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP)
unpublished
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We demonstrate superior performance of a biomedically pretrained BERT model first trained on annotations of a rulebased labeler and then fine-tuned on a small set of expert annotations augmented with automated ...
In this work, we introduce a BERTbased approach to medical image report labeling that exploits both the scale of available rule-based systems and the quality of expert annotations. ...
Thanks to Alistair Johnson for support in the radiologist benchmark, to Jeremy Irvin for support in the CheXpert labeler, Alex Tamkin for helpful comments, and Yifan Peng for helpful feedback. ...
doi:10.18653/v1/2020.emnlp-main.117
fatcat:kbdqwqwelfbyzldxb6xybh57jq
Leveraging Deep Representations of Radiology Reports in Survival Analysis for Predicting Heart Failure Patient Mortality
2021
Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies
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Furthermore, they typically require a large amount of data and high-quality expert annotations for training. ...
In this work, we present a novel method of using BERT-based hidden layer representations of clinical texts as covariates for proportional hazards models to predict patient survival outcomes. ...
Pranav Rajpurkar and Dr. Matthew P Lungren for providing the ChexBert model. ...
doi:10.18653/v1/2021.naacl-main.358
pmid:35463193
pmcid:PMC9034454
fatcat:gfwmdfgl25heze7vjlxcl3oimq
Explaining Chest X-ray Pathologies in Natural Language
[article]
2022
arXiv
pre-print
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Most deep learning algorithms lack explanations for their predictions, which limits their deployment in clinical practice. ...
NLEs are human-friendly and comprehensive, and enable the training of intrinsically explainable models. ...
Acknowledgments We thank Sarim Ather for useful discussions and feedback. M.K. is supported by the EPSRC Center for Doctoral Training in Health Data Science (EP/S02428X/1), and by Elsevier BV. ...
arXiv:2207.04343v1
fatcat:6ivnavxmkbh5jlr5ym3rbnpvly
Making the Most of Text Semantics to Improve Biomedical Vision–Language Processing
[article]
2022
arXiv
pre-print
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and discourse characteristics in radiology reports. ...
Multi-modal data abounds in biomedicine, such as radiology images and reports. Interpreting this data at scale is essential for improving clinical care and accelerating clinical research. ...
, and Dr Matthew Lungren for their clinical input and data annotations provided to this study. ...
arXiv:2204.09817v4
fatcat:c72thidabfbgpgln7yjeoeu6ae
Learning Semi-Structured Representations of Radiology Reports
[article]
2021
arXiv
pre-print
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This paper aims to present an approach for the automatic generation of semi-structured representations of radiology reports. ...
We evaluated the proposed approach on the OpenI corpus of manually annotated chest x-ray radiology reports. ...
Chexbert: combining automatic labelers and expert an-
notations for accurate radiology report labeling using bert. arXiv preprint
arXiv:2004.09167, 2020.
10. ...
arXiv:2112.10746v1
fatcat:sfp4gnodvjepnfga6nidllyxym
Improving Factual Completeness and Consistency of Image-to-Text Radiology Report Generation
[article]
2021
arXiv
pre-print
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Neural image-to-text radiology report generation systems offer the potential to improve radiology reporting by reducing the repetitive process of report drafting and identifying possible medical errors ...
We combine these with the novel use of an existing semantic equivalence metric (BERTScore). We further propose a report generation system that optimizes these rewards via reinforcement learning. ...
Acknowledgements We would like to thank the anonymous reviewers and the members of the Stanford NLP Group for their very helpful comments that substantially improved this paper. ...
arXiv:2010.10042v2
fatcat:7tgoflxc7zburngk44g3ulvsye
Neural Natural Language Processing for Unstructured Data in Electronic Health Records: a Review
[article]
2021
arXiv
pre-print
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Well over half of the information stored within EHRs is in the form of unstructured text (e.g. provider notes, operation reports) and remains largely untapped for secondary use. ...
Despite this central role, EHRs are notoriously difficult to process automatically. ...
CheXbert overcomes this limitation by learning to label radiology reports using both annotations and existing rule-based systems. ...
arXiv:2107.02975v1
fatcat:nayhw7gadfdzrovycdkvzy75pi
Using BERT Models to Label Radiology Reports
2022
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is a radiology resident at New York Presbyterian-Columbia and incoming musculoskeletal radiology fellow at NYU. He previously served on the Radiology: Artificial Intelligence trainee editorial board. ...
He is currently pursuing a Radiological Society of North America Resident Research Grant-funded project to develop a deep learning-based tool to assist radiologists in detecting pediatric upper extremity ...
First, they evaluate how these models perform with small training datasets (CheXbert had 1687 labeled reports and used 75% for training). ...
doi:10.1148/ryai.220124
pmid:35923380
pmcid:PMC9344203
fatcat:ukanxqg4hjbklgj6j6c6zdv2te
Government plans in the 2016 and 2021 Peruvian presidential elections: A natural language processing analysis of the health chapters
2021
Wellcome Open Research
Preserved Fulltext
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Representations from Transformers (KeyBERT), and Rapid Automatic Keywords Extraction (Rake). ...
NLP analysis could also be included in research of health policies and politics during general elections and provide informative summaries for the general population. ...
.: Chexbert:
combining automatic labelers and expert annotations for accurate radiology report labeling using bert . arXiv preprint arXiv: 2004.09167. 2020. ...
doi:10.12688/wellcomeopenres.16867.1
fatcat:q45k6j4qhrhzxptxyriqzmrpcy
Government plans in the 2016 and 2021 Peruvian presidential elections: A natural language processing analysis of the health chapters
2021
Wellcome Open Research
Preserved Fulltext
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Representations from Transformers (KeyBERT), and Rapid Automatic Keywords Extraction (Rake). ...
NLP analysis could also be included in research of health policies and politics during general elections and provide informative summaries for the general population. ...
.:
Chexbert: combining automatic labelers and expert annotations for accurate radiology report labeling using bert . arXiv preprint arXiv: 2004.09167. 2020. ...
doi:10.12688/wellcomeopenres.16867.2
fatcat:f4y6smg2jbamhlk2a26leg6lgu
Improving Factual Completeness and Consistency of Image-to-Text Radiology Report Generation
2021
Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies
unpublished
Preserved Fulltext
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The file type is application/pdf.
Neural image-to-text radiology report generation systems offer the potential to improve radiology reporting by reducing the repetitive process of report drafting and identifying possible medical errors ...
We combine these with the novel use of an existing semantic equivalence metric (BERTScore). We further propose a report generation system that optimizes these rewards via reinforcement learning. ...
Acknowledgements We would like to thank the anonymous reviewers and the members of the Stanford NLP Group for their very helpful comments that substantially improved this paper. ...
doi:10.18653/v1/2021.naacl-main.416
fatcat:qmm7zzojzrezvjmkv6kumttkhm
Referee report. For: Government plans in the 2016 and 2021 Peruvian presidential elections: A natural language processing analysis of the health chapters [version 2; peer review: 1 approved with reservations]
2021
Preserved Fulltext
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and expert annotations for accurate radiology report labeling using bert. ...
.: Chexbert: combining automatic labelers
with self-labelling. 2019. ...
doi:10.21956/wellcomeopenres.19245.r47104
fatcat:rxhyjvdluzddfn72old4ci6wxi
Referee report. For: Government plans in the 2016 and 2021 Peruvian presidential elections: A natural language processing analysis of the health chapters [version 4; peer review: 1 approved]
2022
Preserved Fulltext
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The file type is application/pdf.
Representations from Transformers (KeyBERT), and Rapid Automatic Keywords Extraction (Rake). ...
While clinical medicine has exploded, electronic health records for Natural Language Processing (NLP) analyses, public health, and health policy research have not yet adopted these algorithms. ...
.:
Chexbert: combining automatic labelers and expert annotations for accurate radiology report labeling using bert . arXiv preprint arXiv: 2004.09167. 2020. ...
doi:10.21956/wellcomeopenres.19477.r48096
fatcat:732lhlszhnaize3xw2mogfegaa
Referee report. For: Government plans in the 2016 and 2021 Peruvian presidential elections: A natural language processing analysis of the health chapters [version 3; peer review: 1 approved with reservations]
2022
Preserved Fulltext
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The file type is application/pdf.
Representations from Transformers (KeyBERT), and Rapid Automatic Keywords Extraction (Rake). ...
While clinical medicine has exploded, electronic health records for Natural Language Processing (NLP) analyses, public health, and health policy research have not yet adopted these algorithms. ...
.:
Chexbert: combining automatic labelers and expert annotations for accurate radiology report labeling using bert . arXiv preprint arXiv: 2004.09167. 2020. ...
doi:10.21956/wellcomeopenres.19368.r47709
fatcat:gaevssgy4fhxnnh54zuam4pqa4