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Enhancing systematic review efficiency in hand surgery using artificial intelligence (natural language processing)

Gordon C Wong1, Robert L Kane2, Cheng-C J Chu3

  • 1Section of Plastic Surgery, Department of Surgery, University of Michigan Medical School, Ann Arbor, MI, USA.

The Journal of Hand Surgery, European Volume
|November 15, 2024
PubMed
Summary
This summary is machine-generated.

This study trained a natural language processing (NLP) model to improve hand surgery systematic review screening. The NLP model accelerated abstract screening by 31% without reducing accuracy.

Keywords:
NLPabstractefficiencynatural language processingscreeningsystematic review

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Area of Science:

  • Orthopedic Surgery
  • Medical Informatics
  • Natural Language Processing

Background:

  • Systematic reviews are crucial for evidence-based medicine but are time-consuming.
  • Abstract screening is a major bottleneck in systematic reviews.
  • Automating screening can enhance efficiency and reduce reviewer burden.

Purpose of the Study:

  • To develop and evaluate a natural language processing (NLP) model for screening hand surgery research abstracts.
  • To assess the efficiency gains and accuracy of using NLP in systematic review screening.
  • To identify key text elements in abstracts related to hand surgery interventions and outcomes.

Main Methods:

  • Annotated 1600 hand surgery abstracts for NLP model training.
  • Trained an NLP model to recognize key text elements in research abstracts.
  • Conducted two experiments processing 200 abstracts with NLP assistance for inclusion/exclusion decisions.

Main Results:

  • The NLP model achieved 0.91 accuracy in recognizing key text elements, particularly study interventions.
  • Mean abstract screening time was reduced by 31% using the NLP model.
  • Model precision improved in a second experiment, suggesting context-dependent performance.

Conclusions:

  • NLP models can significantly streamline abstract screening for systematic reviews in hand surgery.
  • This approach enhances efficiency by accurately identifying original research and relevant text.
  • NLP tools offer a promising solution to accelerate evidence synthesis in orthopedic research.