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Area of Science:

  • Medical Informatics
  • Computational Linguistics
  • Radiology Informatics

Background:

  • Natural Language Processing (NLP) enables computers to understand and process human language.
  • NLP applications are common in daily life, such as translation and chatbots.
  • The medical field increasingly uses NLP with the rise of electronic health records.

Purpose of the Study:

  • To explore the applications of NLP in radiology.
  • To highlight non-clinical, provider-focused, and patient-focused uses of NLP in radiology.
  • To discuss challenges and future directions for NLP in radiology.

Main Methods:

  • Review of current NLP techniques and their relevance to radiology.
  • Identification and categorization of existing and potential NLP applications in radiology.
  • Analysis of challenges in NLP development and implementation within radiology.

Main Results:

  • Radiology reports, primarily text-based, are well-suited for NLP applications.
  • Increasing imaging volumes necessitate workflow improvements, where NLP can assist.
  • Numerous NLP applications exist for non-clinical, provider, and patient needs in radiology.

Conclusions:

  • NLP offers significant potential to enhance various aspects of radiology.
  • Addressing challenges is crucial for successful NLP integration in clinical practice.
  • Future directions include further development and broader adoption of NLP tools in radiology.