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Exploring whether ChatGPT-4 with image analysis capabilities can diagnose osteosarcoma from X-ray images.
Ren, Yi; Guo, Yusheng; He, Qingliu; Cheng, Zhixuan; Huang, Qiming; Yang, Lian.
Affiliation
  • Ren Y; Department of Radiology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, No.1277 Jiefang Avenue, Wuhan, 430022, China.
  • Guo Y; Hubei Key Laboratory of Molecular Imaging, Wuhan, 430022, China.
  • He Q; Department of Radiology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, No.1277 Jiefang Avenue, Wuhan, 430022, China.
  • Cheng Z; Hubei Key Laboratory of Molecular Imaging, Wuhan, 430022, China.
  • Huang Q; Department of Urology, The Second Affiliated Hospital of Fujian Medical University, Quanzhou, 362000, China.
  • Yang L; Department of Urology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430022, China.
Exp Hematol Oncol ; 13(1): 71, 2024 Jul 27.
Article in En | MEDLINE | ID: mdl-39068484
ABSTRACT
The generation of radiological results from image data represents a pivotal aspect of medical image analysis. The latest iteration of ChatGPT-4, a large multimodal model that integrates both text and image inputs, including dermatoscopy images, histology images, and X-ray images, has attracted considerable attention in the field of radiology. To further investigate the performance of ChatGPT-4 in medical image recognition, we examined the ability of ChatGPT-4 to recognize credible osteosarcoma X-ray images. The results demonstrated that ChatGPT-4 can more accurately diagnose bone with or without significant space-occupying lesions but has a limited ability to differentiate between malignant lesions in bone compared to adjacent normal tissue. Thus far, the current capabilities of ChatGPT-4 are insufficient to make a reliable imaging diagnosis of osteosarcoma. Therefore, users should be aware of the limitations of this technology.
Key words

Full text: 1 Collection: 01-internacional Database: MEDLINE Language: En Journal: Exp Hematol Oncol Year: 2024 Document type: Article Affiliation country: Country of publication:

Full text: 1 Collection: 01-internacional Database: MEDLINE Language: En Journal: Exp Hematol Oncol Year: 2024 Document type: Article Affiliation country: Country of publication: