Related Experiment Video
Updated: Jul 11, 2026
Measuring 3D In-vivo Shoulder Kinematics using Biplanar Videoradiography
Published on: March 12, 2021
Artificial intelligence-based patient information in rotator cuff injuries: A cross-sectional comparative study of
Bahri Bozgeyik1, Erman Öğümsöğütlü2, Gazi Huri3,4
1Department of Orthopaedics and Traumatology, Faculty of Medicine, Gaziantep University, Gaziantep, Türkiye.
Abstract:
This study aimed to comparatively evaluate the performance of the chat generative pretrained transformer (ChatGPT) and DeepSeek artificial intelligence (AI) models in patient information about rotator cuff injuries. This cross-sectional comparative study was conducted in May 28, 2025 using ChatGPT-4o (OpenAI) and DeepSeek V3 (DeepSeek Inc.) models. Sixteen frequently asked questions related to rotator cuff injuries were posed to both the AI models. The responses were then independently assessed by 2 experienced orthopedic surgeons using the Journal of the American Medical Association (JAMA), response rating system, DISCERN, and 4-point Likert scales. In addition, the readability of the responses was analyzed using the Flesch-Kincaid Readability Score (FRES) and Flesch-Kincaid Grade Level. The primary outcome was overall information quality, secondary outcomes included JAMA benchmark adherence and readability metrics. None of the models met JAMA criteria. In terms of response rating system, there was no statistically significant difference between the 2 models (P >.05). DeepSeek demonstrated higher DISCERN scores compared to ChatGPT (50.12 vs 47.03), with a mean difference of 3.09 (95% CI: 1.58 to 4.61; P = .001). While there was no significant difference in accuracy, clarity, and consistency criteria between the 2 models in the 4-point Likert evaluation (P >.05), DeepSeek scored significantly higher than ChatGPT in the completeness criterion, with a mean difference of 0.75 (95% CI: 0.46 to 1.04; P = .001). In terms of readability, both models showed similar performance (FRES, P >.05; Flesch-Kincaid Grade Level, P >.05). Both AI models deliver satisfactory and clinically relevant information for rotator cuff injury patient education. Although DeepSeek was superior to ChatGPT in terms of completeness of patient information regarding rotator cuff injuries, the results were similar for the other criteria. The responses from both the AI tools were considered promising. However, they require improvements in terms of adherence to scientific standards, transparency, citations, and readability.
