Qualifying certainty in radiology reports through deep learning–based natural language processing
F Liu, P Zhou, SJ Baccei… - American Journal …, 2021 - Am Soc Neuroradiology
BACKGROUND AND PURPOSE: Communication gaps exist between radiologists and
referring physicians in conveying diagnostic certainty. We aimed to explore deep learning …
referring physicians in conveying diagnostic certainty. We aimed to explore deep learning …
RadBERT: adapting transformer-based language models to radiology
Purpose To investigate if tailoring a transformer-based language model to radiology is
beneficial for radiology natural language processing (NLP) applications. Materials and …
beneficial for radiology natural language processing (NLP) applications. Materials and …
Automatic generation of conclusions from neuroradiology MRI reports through natural language processing
P López-Úbeda, T Martín-Noguerol, J Escartín, A Luna - Neuroradiology, 2024 - Springer
Purpose The conclusion section of a radiology report is crucial for summarizing the primary
radiological findings in natural language and essential for communicating results to …
radiological findings in natural language and essential for communicating results to …
Leveraging Professional Radiologists' Expertise to Enhance LLMs' Evaluation for Radiology Reports
In radiology, Artificial Intelligence (AI) has significantly advanced report generation, but
automatic evaluation of these AI-produced reports remains challenging. Current metrics …
automatic evaluation of these AI-produced reports remains challenging. Current metrics …
Deep learning-based natural language processing in radiology: the impact of report complexity, disease prevalence, dataset size, and algorithm type on model …
AW Olthof, PMA van Ooijen, LJ Cornelissen - Journal of medical systems, 2021 - Springer
In radiology, natural language processing (NLP) allows the extraction of valuable
information from radiology reports. It can be used for various downstream tasks such as …
information from radiology reports. It can be used for various downstream tasks such as …
BERT in Radiology: A Systematic Review of Natural Language Processing Applications
Abstract Introduction BERT (Bidirectional Encoder Representations from Transformers),
introduced in 2018, has revolutionized natural language processing (NLP). Its bidirectional …
introduced in 2018, has revolutionized natural language processing (NLP). Its bidirectional …
Bidirectional Encoder Representations from Transformers in Radiology: A Systematic Review of Natural Language Processing Applications
L Gorenstein, E Konen, M Green, E Klang - Journal of the American College …, 2024 - jacr.org
Abstract Introduction Bidirectional Encoder Representations from Transformers (BERT),
introduced in 2018, has revolutionized natural language processing. Its bidirectional …
introduced in 2018, has revolutionized natural language processing. Its bidirectional …
Deep learning to classify radiology free-text reports
Purpose To evaluate the performance of a deep learning convolutional neural network
(CNN) model compared with a traditional natural language processing (NLP) model in …
(CNN) model compared with a traditional natural language processing (NLP) model in …
Domain-adapted large language models for classifying nuclear medicine reports
Purpose To evaluate the impact of domain adaptation on the performance of language
models in predicting five-point Deauville scores on the basis of clinical fluorine 18 …
models in predicting five-point Deauville scores on the basis of clinical fluorine 18 …
Natural language–based machine learning models for the annotation of clinical radiology reports
J Zech, M Pain, J Titano, M Badgeley, J Schefflein… - Radiology, 2018 - pubs.rsna.org
Purpose To compare different methods for generating features from radiology reports and to
develop a method to automatically identify findings in these reports. Materials and Methods …
develop a method to automatically identify findings in these reports. Materials and Methods …
