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Related Concept Videos

Introduction to Language of Pathophysiology l01:25

Introduction to Language of Pathophysiology l

Pathophysiology investigates how biological mechanisms—typically starting at the cellular level—disrupt normal bodily functions. It bridges anatomy and physiology to explain the progression of disease. With this foundation, it is important to understand the following key terms used to describe disease processes: Diagnosis:The process of identifying a disease using clinical evaluation, including signs (objective evidence like rashes), symptoms (subjective experiences like pain), laboratory test...
Introduction to Language of Pathophysiology ll01:17

Introduction to Language of Pathophysiology ll

This lesson explores key terms that describe how diseases progress, their outcomes, and their distribution in populations.Diagnostic tests identify diseases and monitor treatment. These include blood and urine tests, biopsies, imaging (X-ray, MRI), and detection of infectious agents.Remission is a reduction or disappearance of symptoms.Exacerbation refers to the worsening of symptoms, such as increased wheezing during an asthma attack.A precipitating factor triggers an acute episode, while a...

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Related Experiment Video

Updated: Jul 9, 2026

Minimally Invasive Murine Laryngoscopy for Close&#45;Up Imaging of Laryngeal Motion During Breathing and Swallowing
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Systematic Review on Large Language Models in Orthopaedic Surgery.

Kevin Mo1, Rowen Lin2, Evan Dunn1

  • 1Orthopaedic Surgery, Valley Hospital Medical Center, 620 Shadow Ln, Las Vegas, NV 89106, USA.

Journal of Clinical Medicine
|August 28, 2025
PubMed
Summary

Large Language Models (LLMs) show potential in orthopaedic surgery, but current AI accuracy in assessments lags behind orthopaedic residents. Further development is needed for clinical applications.

Keywords:
ChatGPTlarge language modelsorthopaedic surgerysystematic review

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Area of Science:

  • Orthopaedic Surgery
  • Artificial Intelligence
  • Medical Education

Background:

  • The rapid development of Large Language Models (LLMs) since 2022 presents new opportunities in orthopaedic surgery.
  • This systematic review is the first to examine the current research landscape of LLMs in the field.

Purpose of the Study:

  • To identify LLMs researched in orthopaedics.
  • To assess their functionalities and evaluate the quality of their results.
  • To compare LLM performance against orthopaedic residents.

Main Methods:

  • Systematic review conducted using PubMed, Embase, and Cochrane Library.
  • Adherence to Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines.
  • Inclusion of 60 studies evaluating LLMs like ChatGPT, Bard, Perplexity AI, and Bing.

Main Results:

  • ChatGPT 4.0 demonstrated higher accuracy (47.2-73.6% without images) than ChatGPT 3.5 (29.4-55.8% without images).
  • Bard achieved 49.8-58% accuracy; image-based assessments showed lower performance for all LLMs.
  • Orthopaedic residents consistently outperformed LLMs, scoring 74.2-75.3%.

Conclusions:

  • ChatGPT 4.0 significantly improved over ChatGPT 3.5 in orthopaedic assessment accuracy.
  • Orthopaedic residents generally scored higher than current LLMs.
  • Substantial opportunities exist for enhancing LLM performance in orthopaedic assessments, image analysis, and clinical documentation.