GPT-4VGemini Pro Vision,使

Pae Sun Suh1, Woo Hyun Shim1, Chong Hyun Suh1

  • 1From the Department of Radiology and Research Institute of Radiology, University of Ulsan College of Medicine, Asan Medical Center, Olympic-ro 33, Seoul 05505, Republic of Korea (P.S.S., W.H.S., C.H.S., H.J.E., K.J.P., J.C., P.H.K., H.J.P., Y.A., H.Y.P.); Department of Radiology and Research Institute of Radiological Science and Center for Clinical Imaging Data Science, Yonsei University College of Medicine, Seoul, Republic of Korea (P.S.S.); Department of Medical Science, University of Ulsan College of Medicine, Asan Medical Institute of Convergence Science and Technology, Seoul, Republic of Korea (W.H.S., H.H., C.R.P.); Medical Research Institute, Ganneung Asan Hospital, University of Ulsan College of Medicine, Gangneung, Republic of Korea (Y.C.); Department of Internal Medicine, University of Ulsan College of Medicine, Asan Medical Center, Seoul, Republic of Korea (C.Y.W.); and Department of Pulmonary and Critical Care Medicine, Gumdan Top Hospital, Incheon, Republic of Korea (H.P.).

Radiology
|July 9, 2024
PubMed
概括

像GPT-4V和Gemini Pro Vision这样的大型语言模型 (LLM) 在分析医疗图像时,在更高的温度设置下显示出更好的诊断准确性. 虽然放射科医生仍然优于LLMs,但GPT-4V显示出作为诊断支持工具的希望.