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Daiju Ueda

Showing results (41-50 of 97) with videos related to

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Neuroradiology|November 23, 2023
Accuracy of ChatGPT generated diagnosis from patient's medical history and imaging findings in neuroradiology casesDaisuke Horiuchi, Hiroyuki Tatekawa, Taro Shimono, et al.
Japanese Journal of Radiology|June 10, 2024
Data set terminology of deep learning in medicine: a historical review and recommendationShannon L Walston, Hiroshi Seki, Hirotaka Takita, et al.
Radiology|August 1, 2023
AI-based Virtual Synthesis of Methionine PET from Contrast-enhanced MRI: Development and External Validation StudyHirotaka Takita, Toshimasa Matsumoto, Hiroyuki Tatekawa, et al.
European Radiology|July 12, 2024
ChatGPT's diagnostic performance based on textual vs. visual information compared to radiologists' diagnostic performance in musculoskeletal radiologyDaisuke Horiuchi, Hiroyuki Tatekawa, Tatsushi Oura, et al.
Insights Into Imaging|March 16, 2026
Insufficient reporting quality in large language model studies in the field of radiologyPae Sun Suh, So Yeong Jeong, Daiju Ueda, et al.
Radiology|October 24, 2018
Deep Learning for MR Angiography: Automated Detection of Cerebral AneurysmsDaiju Ueda, Akira Yamamoto, Masataka Nishimori, et al.
Japanese Journal of Radiology|March 8, 2025
Evaluation of radiology residents' reporting skills using large language models: an observational studyNatsuko Atsukawa, Hiroyuki Tatekawa, Tatsushi Oura, et al.
European Journal of Radiology|July 14, 2022
Visual and quantitative evaluation of microcalcifications in mammograms with deep learning-based super-resolutionTakashi Honjo, Daiju Ueda, Yutaka Katayama, et al.
Japanese Journal of Radiology|January 15, 2025
Recent trends in scientific research in chest radiology: What to do or not to do? That is the critical question in researchHiroto Hatabu, Masahiro Yanagawa, Yoshitake Yamada, et al.
The Lancet. Digital Health|July 8, 2023
Artificial intelligence-based model to classify cardiac functions from chest radiographs: a multi-institutional, retrospective model development and validation studyDaiju Ueda, Toshimasa Matsumoto, Shoichi Ehara, et al.
Pageof 10

Showing results (41-50 of 97) with videos related to

Sort By:
Pageof 10
Neuroradiology|November 23, 2023
Accuracy of ChatGPT generated diagnosis from patient's medical history and imaging findings in neuroradiology casesDaisuke Horiuchi, Hiroyuki Tatekawa, Taro Shimono, et al.
Japanese Journal of Radiology|June 10, 2024
Data set terminology of deep learning in medicine: a historical review and recommendationShannon L Walston, Hiroshi Seki, Hirotaka Takita, et al.
Radiology|August 1, 2023
AI-based Virtual Synthesis of Methionine PET from Contrast-enhanced MRI: Development and External Validation StudyHirotaka Takita, Toshimasa Matsumoto, Hiroyuki Tatekawa, et al.
European Radiology|July 12, 2024
ChatGPT's diagnostic performance based on textual vs. visual information compared to radiologists' diagnostic performance in musculoskeletal radiologyDaisuke Horiuchi, Hiroyuki Tatekawa, Tatsushi Oura, et al.
Insights Into Imaging|March 16, 2026
Insufficient reporting quality in large language model studies in the field of radiologyPae Sun Suh, So Yeong Jeong, Daiju Ueda, et al.
Radiology|October 24, 2018
Deep Learning for MR Angiography: Automated Detection of Cerebral AneurysmsDaiju Ueda, Akira Yamamoto, Masataka Nishimori, et al.
Japanese Journal of Radiology|March 8, 2025
Evaluation of radiology residents' reporting skills using large language models: an observational studyNatsuko Atsukawa, Hiroyuki Tatekawa, Tatsushi Oura, et al.
European Journal of Radiology|July 14, 2022
Visual and quantitative evaluation of microcalcifications in mammograms with deep learning-based super-resolutionTakashi Honjo, Daiju Ueda, Yutaka Katayama, et al.
Japanese Journal of Radiology|January 15, 2025
Recent trends in scientific research in chest radiology: What to do or not to do? That is the critical question in researchHiroto Hatabu, Masahiro Yanagawa, Yoshitake Yamada, et al.
The Lancet. Digital Health|July 8, 2023
Artificial intelligence-based model to classify cardiac functions from chest radiographs: a multi-institutional, retrospective model development and validation studyDaiju Ueda, Toshimasa Matsumoto, Shoichi Ehara, et al.
Pageof 10