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 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.

Automated summary

Natural Language Processing (NLP) has emerged as a valuable tool in diagnostic radiology, particularly in breast imaging. This comprehensive review discusses the recent advances in NLP for breast imaging, including techniques for extracting relevant information from clinical notes, radiology reports, and pathology reports. It also explores the potential impact of NLP on the accuracy and efficiency of breast imaging and highlights the challenges and opportunities for NLP in this field. Overall, this review emphasizes the potential of NLP in enhancing breast imaging care and provides valuable insights for clinicians and researchers.