Natural Language Processing for Breast Imaging: A Systematic Review
Natural Language Processing (NLP) has gained prominence in diagnostic radiology, offering a promising tool for improving breast imaging triage, diagnosis, lesion characterization, and treatment management in breast cancer and other breast diseases. This review provides a comprehensive overview of re...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2023-04-01
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| Series: | Diagnostics |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2075-4418/13/8/1420 |
| _version_ | 1827745373890805760 |
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| author | Kareem Mahmoud Diab Jamie Deng Yusen Wu Yelena Yesha Fernando Collado-Mesa Phuong Nguyen |
| author_facet | Kareem Mahmoud Diab Jamie Deng Yusen Wu Yelena Yesha Fernando Collado-Mesa Phuong Nguyen |
| author_sort | Kareem Mahmoud Diab |
| collection | DOAJ |
| description | Natural Language Processing (NLP) has gained prominence in diagnostic radiology, offering a promising tool for improving breast imaging triage, diagnosis, lesion characterization, and treatment management in breast cancer and other breast diseases. This review provides a comprehensive overview of recent advances in NLP for breast imaging, covering the main techniques and applications in this field. Specifically, we discuss various NLP methods used to extract relevant information from clinical notes, radiology reports, and pathology reports and their potential impact on the accuracy and efficiency of breast imaging. In addition, we reviewed the state-of-the-art in NLP-based decision support systems for breast imaging, highlighting the challenges and opportunities of NLP applications for breast imaging in the future. Overall, this review underscores the potential of NLP in enhancing breast imaging care and offers insights for clinicians and researchers interested in this exciting and rapidly evolving field. |
| first_indexed | 2024-03-11T05:06:10Z |
| format | Article |
| id | doaj.art-801ba3eabbd94c7a97b5eaa893b5222a |
| institution | Directory Open Access Journal |
| issn | 2075-4418 |
| language | English |
| last_indexed | 2024-03-11T05:06:10Z |
| publishDate | 2023-04-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Diagnostics |
| spelling | doaj.art-801ba3eabbd94c7a97b5eaa893b5222a2023-11-17T18:54:51ZengMDPI AGDiagnostics2075-44182023-04-01138142010.3390/diagnostics13081420Natural Language Processing for Breast Imaging: A Systematic ReviewKareem Mahmoud Diab0Jamie Deng1Yusen Wu2Yelena Yesha3Fernando Collado-Mesa4Phuong Nguyen5Institute for Data Science and Computing, University of Miami, Miami, FL 33146, USADepartment of Computer Science, University of Miami, Miami, FL 33146, USAInstitute for Data Science and Computing, University of Miami, Miami, FL 33146, USAInstitute for Data Science and Computing, University of Miami, Miami, FL 33146, USADepartment of Radiology, Miller School of Medicine, University of Miami, Miami, FL 33146, USAInstitute for Data Science and Computing, University of Miami, Miami, FL 33146, USANatural Language Processing (NLP) has gained prominence in diagnostic radiology, offering a promising tool for improving breast imaging triage, diagnosis, lesion characterization, and treatment management in breast cancer and other breast diseases. This review provides a comprehensive overview of recent advances in NLP for breast imaging, covering the main techniques and applications in this field. Specifically, we discuss various NLP methods used to extract relevant information from clinical notes, radiology reports, and pathology reports and their potential impact on the accuracy and efficiency of breast imaging. In addition, we reviewed the state-of-the-art in NLP-based decision support systems for breast imaging, highlighting the challenges and opportunities of NLP applications for breast imaging in the future. Overall, this review underscores the potential of NLP in enhancing breast imaging care and offers insights for clinicians and researchers interested in this exciting and rapidly evolving field.https://www.mdpi.com/2075-4418/13/8/1420Natural Language Processingbreast imagingbreast cancerradiology reportspathology reportssystematic review |
| spellingShingle | Kareem Mahmoud Diab Jamie Deng Yusen Wu Yelena Yesha Fernando Collado-Mesa Phuong Nguyen Natural Language Processing for Breast Imaging: A Systematic Review Diagnostics Natural Language Processing breast imaging breast cancer radiology reports pathology reports systematic review |
| title | Natural Language Processing for Breast Imaging: A Systematic Review |
| title_full | Natural Language Processing for Breast Imaging: A Systematic Review |
| title_fullStr | Natural Language Processing for Breast Imaging: A Systematic Review |
| title_full_unstemmed | Natural Language Processing for Breast Imaging: A Systematic Review |
| title_short | Natural Language Processing for Breast Imaging: A Systematic Review |
| title_sort | natural language processing for breast imaging a systematic review |
| topic | Natural Language Processing breast imaging breast cancer radiology reports pathology reports systematic review |
| url | https://www.mdpi.com/2075-4418/13/8/1420 |
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