Maintenance Notice

Due to necessary scheduled maintenance, the JMIR Publications website will be unavailable from Wednesday, July 01, 2020 at 8:00 PM to 10:00 PM EST. We apologize in advance for any inconvenience this may cause you.

Who will be affected?

Accepted for/Published in: JMIR Medical Informatics

Date Submitted: May 11, 2023
Open Peer Review Period: May 11, 2023 - Jul 6, 2023
Date Accepted: Aug 25, 2023
(closed for review but you can still tweet)

The final, peer-reviewed published version of this preprint can be found here:

Applications of the Natural Language Processing Tool ChatGPT in Clinical Practice: Comparative Study and Augmented Systematic Review

Schopow N, Osterhoff G, Baur D

Applications of the Natural Language Processing Tool ChatGPT in Clinical Practice: Comparative Study and Augmented Systematic Review

JMIR Med Inform 2023;11:e48933

DOI: 10.2196/48933

PMID: 38015610

PMCID: 10716749

NLP Applications in Clinical Practice: A Comparative Study and Augmented Systematic Review with ChatGPT

  • Nikolas Schopow; 
  • Georg Osterhoff; 
  • David Baur

ABSTRACT

Background:

This research integrates a comparative analysis of the performance of human researchers and OpenAI's ChatGPT in systematic review tasks and an assessment of the application of Natural Language Processing (NLP) models in clinical practice through a review of five studies.

Objective:

The objective of this study is dual: to evaluate the reliability between ChatGPT and human researchers in extracting key information from clinical articles, and to investigate the practical use of NLP in clinical settings as evidenced by selected studies.

Methods:

The study design comprised a systematic review of clinical articles executed independently by human researchers and ChatGPT. The level of agreement between and within raters for parameter extraction was assessed using Fleiss' and Cohen's kappa statistics.

Results:

The comparative analysis revealed a high degree of concordance between ChatGPT and human researchers for most parameters, with less agreement for study design, clinical task, and clinical implementation. The review identified five significant studies that demonstrated the diverse applications of NLP in clinical settings. The findings from these studies highlighted the potential of NLP to improve clinical efficiency and patient outcomes in various contexts, from enhancing allergy detection and classification to improving quality metrics in psychotherapy treatments for veterans with PTSD.

Conclusions:

The results underscore the potential of NLP models, including ChatGPT, in performing systematic reviews and other clinical tasks. Despite certain limitations, NLP presents a promising avenue for enhancing healthcare efficiency and accuracy. Future research should concentrate on broadening the range of clinical applications and exploring the ethical considerations of using NLP in healthcare settings. Clinical Trial: PROSPERO: CRD42023401683


 Citation

Please cite as:

Schopow N, Osterhoff G, Baur D

Applications of the Natural Language Processing Tool ChatGPT in Clinical Practice: Comparative Study and Augmented Systematic Review

JMIR Med Inform 2023;11:e48933

DOI: 10.2196/48933

PMID: 38015610

PMCID: 10716749

Download PDF


Request queued. Please wait while the file is being generated. It may take some time.

© The authors. All rights reserved. This is a privileged document currently under peer-review/community review (or an accepted/rejected manuscript). Authors have provided JMIR Publications with an exclusive license to publish this preprint on it's website for review and ahead-of-print citation purposes only. While the final peer-reviewed paper may be licensed under a cc-by license on publication, at this stage authors and publisher expressively prohibit redistribution of this draft paper other than for review purposes.