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Natural Language Processing: from Bedside to Everywhere.

Eiji Aramaki1, Shoko Wakamiya1, Shuntaro Yada1

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Summary
This summary is machine-generated.

Natural Language Processing (NLP) is advancing in medicine, but a gap exists between research and practical applications. This study reviews medical NLP applications and identifies challenges for bedside use.

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Area of Science:

  • Medical Informatics
  • Natural Language Processing (NLP)

Background:

  • The rapid advancement of Natural Language Processing (NLP) has increased its relevance in the medical field.
  • Despite numerous publications, a significant gap persists between fundamental NLP research and practical product development in healthcare.

Purpose of the Study:

  • To bridge the gap between NLP research and practical medical product development.
  • To clarify the achievements of medical NLP across various medical fields.
  • To identify the challenges hindering the practical application of NLP in medicine.

Main Methods:

  • A comprehensive literature review was conducted.
  • Exploration of potential NLP products and services across diverse medical, clinical, and healthcare domains.

Main Results:

  • Clinical applications of NLP, termed "bedside applications," were detailed for various departments including internal medicine, pre-surgery, post-surgery, oncology, radiology, pathology, psychiatry, rehabilitation, obstetrics, and gynecology.
  • Technical challenges impeding the widespread adoption of NLP for bedside applications were identified.

Conclusions:

  • The findings facilitate discussions on feasible NLP applications in healthcare.
  • Identified research gaps will guide future studies in medical NLP.