Improving Neurology Clinical Care With Natural Language Processing Tools.

Area of Science:

• Neurology
• Medical Informatics
• Artificial Intelligence

Background:

• Natural Language Processing (NLP) tools offer potential benefits for clinical care.
• Transformer-based NLP algorithms (e.g., GPT, BERT) show promise in augmenting neurology workflows.

Purpose of the Study:

• To explore the integration of NLP tools into neurology.
• To identify the potential benefits, risks, and barriers of implementing NLP in clinical neurology.

Main Methods:

• Review of recent advances in transformer-based NLP algorithms.
• Analysis of potential applications in summarizing patient health information, suggesting care options, and assisting research.
• Consideration of implementation barriers and risks such as data security and fabricated facts.

Main Results:

• NLP can enhance neurology by summarizing patient data, suggesting treatments, and aiding research on large datasets.
• Potential risks include data security breaches and the generation of inaccurate information.
• Significant barriers to implementation exist within clinical settings.

Conclusions:

• Despite risks and barriers, NLP integration offers substantial benefits for neurology providers, patients, and communities.
• The increasing functionality of NLP systems and medical needs may make integration essential.
• Further research is needed to develop strategies for effective implementation, risk mitigation, and barrier overcoming.