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Yuki Shimahara

Showing results (1-10 of 10) with videos related to

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Scientific Reports|January 15, 2022
Deep learning-based algorithm for lung cancer detection on chest radiographs using the segmentation methodAkitoshi Shimazaki, Daiju Ueda, Antoine Choppin, et al.
Plos One|February 23, 2019
IMACEL: A cloud-based bioimage analysis platform for morphological analysis and image classificationYuki Shimahara, Ko Sugawara, Kei H Kojo, et al.
Medicine|October 30, 2020
Incidental cerebral aneurysms detected by a computer-assisted detection system based on artificial intelligence: A case seriesYuki Shimada, Tetsuya Tanimoto, Masataka Nishimori, et al.
BMC Bioinformatics|April 27, 2021
MADGAN: unsupervised medical anomaly detection GAN using multiple adjacent brain MRI slice reconstructionChanghee Han, Leonardo Rundo, Kohei Murao, et al.
Diagnostics (Basel, Switzerland)|October 23, 2021
Detection Accuracy and Latency of Colorectal Lesions with Computer-Aided Detection System Based on Low-Bias EvaluationHiroaki Matsui, Shunsuke Kamba, Hideka Horiuchi, et al.
Radiology|October 24, 2018
Deep Learning for MR Angiography: Automated Detection of Cerebral AneurysmsDaiju Ueda, Akira Yamamoto, Masataka Nishimori, et al.
Scientific Reports|May 2, 2024
Artificial intelligence for volumetric measurement of cerebral white matter hyperintensities on thick-slice fluid-attenuated inversion recovery (FLAIR) magnetic resonance images from multiple centersMasashi Kuwabara, Fusao Ikawa, Shinji Nakazawa, et al.
Journal of Gastroenterology|July 4, 2021
Reducing adenoma miss rate of colonoscopy assisted by artificial intelligence: a multicenter randomized controlled trialShunsuke Kamba, Naoto Tamai, Iduru Saitoh, et al.
Scientific Reports|September 27, 2023
Effectiveness of tuning an artificial intelligence algorithm for cerebral aneurysm diagnosis: a study of 10,000 consecutive casesMasashi Kuwabara, Fusao Ikawa, Shigeyuki Sakamoto, et al.
Nature Communications|September 22, 2023
Seasonal pigment fluctuation in diploid and polyploid Arabidopsis revealed by machine learning-based phenotyping method PlantServationReiko Akiyama, Takao Goto, Toshiaki Tameshige, et al.
Pageof 1

Showing results (1-10 of 10) with videos related to

Sort By:
Pageof 1
Scientific Reports|January 15, 2022
Deep learning-based algorithm for lung cancer detection on chest radiographs using the segmentation methodAkitoshi Shimazaki, Daiju Ueda, Antoine Choppin, et al.
Plos One|February 23, 2019
IMACEL: A cloud-based bioimage analysis platform for morphological analysis and image classificationYuki Shimahara, Ko Sugawara, Kei H Kojo, et al.
Medicine|October 30, 2020
Incidental cerebral aneurysms detected by a computer-assisted detection system based on artificial intelligence: A case seriesYuki Shimada, Tetsuya Tanimoto, Masataka Nishimori, et al.
BMC Bioinformatics|April 27, 2021
MADGAN: unsupervised medical anomaly detection GAN using multiple adjacent brain MRI slice reconstructionChanghee Han, Leonardo Rundo, Kohei Murao, et al.
Diagnostics (Basel, Switzerland)|October 23, 2021
Detection Accuracy and Latency of Colorectal Lesions with Computer-Aided Detection System Based on Low-Bias EvaluationHiroaki Matsui, Shunsuke Kamba, Hideka Horiuchi, et al.
Radiology|October 24, 2018
Deep Learning for MR Angiography: Automated Detection of Cerebral AneurysmsDaiju Ueda, Akira Yamamoto, Masataka Nishimori, et al.
Scientific Reports|May 2, 2024
Artificial intelligence for volumetric measurement of cerebral white matter hyperintensities on thick-slice fluid-attenuated inversion recovery (FLAIR) magnetic resonance images from multiple centersMasashi Kuwabara, Fusao Ikawa, Shinji Nakazawa, et al.
Journal of Gastroenterology|July 4, 2021
Reducing adenoma miss rate of colonoscopy assisted by artificial intelligence: a multicenter randomized controlled trialShunsuke Kamba, Naoto Tamai, Iduru Saitoh, et al.
Scientific Reports|September 27, 2023
Effectiveness of tuning an artificial intelligence algorithm for cerebral aneurysm diagnosis: a study of 10,000 consecutive casesMasashi Kuwabara, Fusao Ikawa, Shigeyuki Sakamoto, et al.
Nature Communications|September 22, 2023
Seasonal pigment fluctuation in diploid and polyploid Arabidopsis revealed by machine learning-based phenotyping method PlantServationReiko Akiyama, Takao Goto, Toshiaki Tameshige, et al.
Pageof 1