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Natural Language Processing: Chances and Challenges in Dentistry.

Martha Büttner1, Ulf Leser2, Lisa Schneider1

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Summary
This summary is machine-generated.

Natural language processing (NLP) offers significant potential in dentistry for tasks like symptom classification and chatbots. However, data requirements and challenges in explainability currently limit its widespread adoption in the dental field.

Keywords:
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Area of Science:

  • * Computer Science and Linguistics
  • * Natural Language Processing (NLP)

Background:

  • * NLP enables machines to process and understand human language.
  • * Applications in dentistry include text classification and natural language generation/understanding.
  • * NLP can analyze large text volumes for disease insights and personalized care.

Purpose of the Study:

  • * To summarize the applications of NLP in dentistry.
  • * To outline the limitations of NLP in the dental domain.
  • * To call for community action to improve dental NLP.

Main Methods:

  • * Narrative review of existing literature.
  • * Analysis of current NLP applications and technologies.
  • * Identification of challenges and potential solutions for NLP in dentistry.

Main Results:

  • * Key NLP applications include symptom classification, clinical chatbots, and speech recognition for documentation.
  • * Advanced NLP technologies like Recurrent Neural Networks and Transformers show promise but are data-hungry.
  • * Current dental NLP research primarily uses rule-based solutions for narrow tasks.

Conclusions:

  • * NLP is poised to become a cornerstone in various dental applications.
  • * Overcoming limitations through federated learning, transfer learning, or data sharing is crucial.
  • * Addressing challenges in explainability, reproducibility, and generalizability is necessary for medical device approval.