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Exploring whether ChatGPT-4 with image analysis capabilities can diagnose osteosarcoma from X-ray images

Yi Ren, Yusheng Guo, Qingliu He, Zhixuan Cheng, Qiming Huang, Lian Yang

2024Experimental Hematology and Oncology19 citationsDOIOpen Access PDF

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.

Topics & Concepts

OsteosarcomaComputer scienceImage qualityArtificial intelligenceRadiological weaponRadiologyComputer visionMedicineImage (mathematics)PathologyArtificial Intelligence in Healthcare and EducationRadiomics and Machine Learning in Medical ImagingMachine Learning in Healthcare
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