Natural language processing in radiology: Clinical applications and future directions

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.