T. Matsumoto, S. Terai, T. Oishi, S. Kuwashiro , K. Fujisawa, N. Yamamoto, Y. Fujita, Y. Hamamoto, M, Furutani-Seiki, H. Nishina and I. Sakaida : Medaka as a model for human nonalcoholic steatohepatitis , Disease Models & Mechanisms, 3, 431-440, 2010
N. Iizuka, M. Oka, I. Sakaida , T. Moribe , T. Miura, N. Kimura, S. Tamatsukuri , H. Ishitsuka, K. Uchida, S. Terai, S. Yamashita, K. Okita, K. Sakata, Y. Karino, J. Toyota, E. Ando, T. Ide, M. Sata, R. Tsunedomi , M. Tsutsui, M. Iida, Y. Tokuhisa , K. Sakamoto, T. Tamesa, Y. Fujita and Y. Hamamoto : Efficient detection of hepatocellular carcinoma by a hybrid blood test of epigenetic and classical protein markers , Clinica Chimica Acta, 412, 1-2, pp.152-158, 2011
S. Hazama, H. Takenouchi , R. Tsunedomi , M. Iida, N. Suzuki, N. Iizuka, Y. Inoue, K. Sakamoto, M. Nakao, Y. Shindo, S. Kanekiyo , Y. Tokumitsu , K. Yoshimura, N. Maeda, K. Maeda, Y. Maeda, H. Matsui, S. Yoshino, Y. Nakamura, Y. Fujita, Y. Hamamoto, M. Okamoto, T. Fujita, Y. Kawakami, and M. Oka : Predictive Biomarkers for the Outcome of Vaccination of Five Therapeutic Epitope Peptides for Colorectal Cancer , Anticancer Research, 34, 8, 4201-4206, 2014
H. Tanaka, S. Hazama, M. Iida, R. Tsunedomi , H. Takenouchi , M. Nakajima, Y. Tokumitsu , S. Kanekiyo , Y. Shindo, S. Tomochika, Y. Tokuhisa , K. Sakamoto, N. Suzuki, S. Takeda, S. Yamamoto, S. Yoshino, T. Ueno, Y. Hamamoto, Y. Fujita, H. Tanaka, K. Tahara , R. Shimizu, K. Okuno, K. Fujita, M. Kuroda, Y. Nakamura, and H. Nagano: miR-125b-1 and miR-378a are Predictive Biomarkers for the Efficacy of Vaccine Treatment against Colorectal Cancer , Cancer Science, 108, 11, 2229-2238, 2017
N. Iizuka, H. Nakae, M. Segawa, K. Tanaka, Y. Fujita, H. Ogihara , K. Nakahara, E. Takeo, K. Itasaka , N. Hasunuma , Y. Hamamoto : Web‐based evaluation system for closing the education gap in Kampo medicine between facilities , Traditional & Kampo Medicine, 6, 1, 12-18, 2019
Y. Mitani, Y. Fujita, and Y. Hamamoto: Augmentation on CNNs for Handwritten Digit Classification in a Small Training Sample Size Situation , Journal of Physics Conference Series, 1992, 012007, 6 pages, 2021
Y. Mitani, N. Yamaguchi, Y. Fujita, and Y. Hamamoto: Evaluation of Transfer Learning for a Handwritten Character Classification with Small Training Samples , Journal of Image and Graphics, 11, 1, 21-25, 2023
Y. Fujita , T. Tanaka, T. Hori and Y. Hamamoto: Classification Model based on U-Net for Crack Detection from Asphalt Pavement Images , Journal of Image and Graphics, 11, 2, 121-126, 2023
Y. Mitani, Y. Fujita, N. Matsunaga, and Y. Hamamoto: Feature selection methods of the combined feature vector for classifying diffuse lung opacities in thin section computed tomography , IEEE EMBS Asian-Pacific Conference on Biomedical Engineering 2003, Keihanna 2003
Y. Mitani, Y. Fujita, N. Matsunaga, and Y. Hamamoto: A study on Nonparametric Classifiers for a CAD System of Diffuse Lung Opacities in Thin-Section Computed Tomography Images , Knowledge-Based Intelligent Information & Engineering Systems, M. Gh . Negoita et al. (Eds.), Springer-Verlag, Lecture Notes in Artificial Intelligence 3213, Part I, 608-613, 2004
Y. Fujita , Y. Mitani and Y. Hamamoto: A Method for Crack Detection on a Concrete Structure , 18th International Conference on Pattern Recognition (ICPR2006), Proceedings of 18th International Conference on Pattern Recognition (ICPR2006), Vol.3, pp.901-904, 2006. Citation: 286 (Google Scholar), 197 (Scopus) 2026/6/26
Y. Fujita and Y. Hamamoto: A Robust Method for Automatically Detecting Cracks on Noisy Concrete Surfaces , The Twenty Second International Conference on Industrial, Engineering & Other Applications of Applied Intelligent Systems 2009 (IEA/AIE 2009), Lecture Notes in Artificial Intelligence 5579, 76-85, 2009
K. Ogashiwa , Y. Hamamoto, Y. Fujita, K. Murokawa , H. Yoneda, M. Saito, S. Terai and I. Sakaida : On a Diagnostic Imaging Teaching System for Endoscopic Education , 1st Asia Pacific Conference on Health Promotion and Education, Proceedings of 1st Asia Pacific Conference on Health Promotion and Education, Chiba, 2009
Y. Fujita , Y. Hamamoto, M. Segawa, S. Terai and I. Sakaida : An Improved Method for Cirrhosis Detection using Liver’s Ultrasound Images , 20th International Conference on Pattern Recognition (ICPR2010), Proceedings of 20th International Conference on Pattern Recognition (ICPR2010), 2294-2297, 2010
Y. Mitani, Y. Fujita, N. Matsunaga and Y. Hamamoto: The Use of a Local Histogram Feature Vector of Classifying Diffuse Lung Opacities in High-Resolution Computed Tomography , 25th International Conference on Industrial, Engineering & Other Applications of Applied Intelligent Systems 2012 (IEA/AIE 2012), Lecture Notes in Artificial Intelligence 7345, Advanced Research in Applied Artificial Intelligence, 343-350, 2012
T. Kanemura, Y. Mitani, Y. Fujita and Y. Hamamoto: A Note of Fingerspelling Recognition by Hand Shape Using Higher-Order Local Auto-Correlation Features , SICE Annual Conference 2012, Proc, of SICE Annual Conference 2012, 777-778, 2012
Y. Mitani, T. Kanemura, Y. Fujita and Y. Hamamoto: A Study of Fingerspelling Recognition by Hand Shape Using a Histogram of Oriented Gradient Feature Vector , 11th International Conference on Quality Control by Artificial Vision (QCAV2013), Proceedings of 11th International Conference on Quality Control by Artificial Vision (QCAV2013), 22-25, 2013
Y. Fujita , T. Goto, Y. Mitani, Y. Hamamoto, M. Segawa, S. Terai, and I. Sakaida : A liver cirrhosis detection method using probabilistic ROI combination , 11th International Conference on Quality Control by Artificial Vision (QCAV2013), Proceedings of 11th International Conference on Quality Control by Artificial Vision (QCAV2013), 81-85, 2013
K. Fujino, Y. Mitani, T. Hayashi, Y. Fujita, Y. Hamamoto, M. Segawa, S. Terai, and I. Sakaida : A Study of Liver Cirrhosis Classification on M-mode Ultrasound Images by Higher-Order Local Auto-Correlation Features , SICE Annual Conference 2013, Proceedings of SICE Annual Conference 2013, 1403-1404, 2013
M. Suenaga, Y. Fujita, S. Hashimoto, T. Shuji, I. Sakaida , and Y. Hamamoto: A Method of Bubble Removal for Computer-Assisted Diagnosis of Capsule Endoscopic Images , Proceedings on 27th International Conference on Industrial Engineering and Other Applications of Applied Intelligent Systems (IEA/AIE 2014), Modern Advances in Applied Intelligence, Lecture Notes in Computer Science (LNCS), 8482, 228-233, 2014
H. Ogihara , Y. Fujita, N. Iizuka, M. Oka, and, Y. Hamamoto: Comparative Study of Classifiers for Prediction of Recurrence of Liver Cancer Using Binary Batterns , Proceedings on 27th International Conference on Industrial Engineering and Other Applications of Applied Intelligent Systems (IEA/AIE 2014), Modern Advances in Applied Intelligence, Lecture Notes in Computer Science (LNCS), 8482, 234-239, 2014
Y. Fujita , Y. Mitani, Y. Hamamoto, M. Segawa, S. Terai, and I. Sakaida : Training ROI Selection Based on MILBoost for Liver Cirrhosis Classification Using Ultrasound Images , Proceedings of 29th International Conference on Industrial Engineering and Other Applications of Applied Intelligent Systems (IEA/AIE 2016), Trends in Applied Knowledge-Based Systems and Data Science, Lecture Notes in Computer Science (LNCS), 9799, 451-459, 2016
T. Kawamura, M. Fukushi, Y. Hirano, Y. Fujita, and Y. Hamamoto: An NTP-based Detection Module for DDoS Attacks on IoT , Proceedings of IEEE International Conference on Consumer Electronics Taiwan (ICCE-TW), 15-16, 2017
T. Kawamura, M. Fukushi, Y. Hirano, Y. Fujita, and Y. Hamamoto: The Network-based Event Detection Module by NTP for Cyber Attacks on IoT , Proceedings of CANDAR 2018, 6 pages, 2018
Y. Mitani, Y. Fujita, N. Matsunaga, and Y. Hamamoto: Evaluation of feature selection methods for classifying diffuse lung opacities in thin-section computed tomography images, Radiological Society of North America, 89th Scientific Assembly and Annual Meeting, p.50, Chicago, Dec. 2003.
Y. Mitani, Y. Fujita, N. Matsunaga, and Y. Hamamoto: A Consideration of artificial images for classifying diffuse lung opacities in thin-section computed tomography images, Radiological Society of North America, 89th Scientific Assembly and Annual Meeting, p.646, Chicago, Dec. 2003
Y. Fujita , T. Miyamoto, Y. Hamamoto, N. Iizuka and M. Oka: The Fisher ratio is an effective means for biomarker identification, compared with the Mann-Whitney ’ s test, 68th Annual Meeting of the Japanese Cancer Association, p.508, Yokohama, Oct. 2009
S. Hazama, Y. Hinoda , N. Okayama, Y. Hamamoto, Y. Fujita, H. Mishima, U. Sakamoto and M. Oka: Genotype subset selection of UGT1As polymorphisms can predict toxicity and tumor response of mCRC pts received FOLFIRI, 68th Annual Meeting of the Japanese Cancer Association, p.379, Yokohama, Oct. 2009
S. Hazama, M. Oka, Y. Hamamoto, Y. Fujita, Y. Hinoda , N. Okayama, Y. Okuyama, T. Kato, H. Mishima, and J. Sakamoto: Genotype subset selection of multi-UGT1As polymorphisms can predict severe neutropenia and tumor responses of metastatic CRC patients received FOLFIRI regimen, Abstract Book Joint ECCO 15 34th ESMO Multidisciplinary Congress BERLIN, European Journal of Cancer Supplements, 7, 2, p.354, Sep. 2009
S. Hazama, Y. Okuyama, T. Kato, N. Okayama, Y. Hinoda , J. Sakamoto, H. Mishima, Y. Fujita, Y. Hamamoto, and M. Oka: Use of genotype subset selections of multi-UGT1As polymorphisms to predict severe neutropenia and tumor responses of metastatic CRC patients received FOLFIRI regimen, 2009 ASCO Annual Meeting, e15038, 2009
Y. Fujita , Y. Hamamoto, N. Iizuka, T. Moribe and M. Oka: An optimized Fisher liner classifier for detection of hepatocellular carcinoma, American Association for Cancer Research-Japanese Cancer Association (AACR-JCA) 8th Joint Conference, Cancer Genomics, Epigenomics, and the Development of Novel Therapeutics, Feb. 2010
Y. Fujita , Y. Hamamoto, S. Hazama, Y. Hinoda , N. Okayama and M. Oka: Accurate predictor designed by genotype subset selection to predict severe toxicities and tumor responses to irinotecan, 69th Annual Meeting of the Japanese Cancer Association, p.198, Osaka, Sep. 2010
門 祥平 ,藤田 悠介,浜本 義彦,瀬川 誠,寺井 崇二,坂井田 功:超音波画像を用いた肝硬変診断のための半教師付き学習の適用, IEEE Consumer Electronics Society West Japan Joint Chapter 研究会, IEEE Consumer Electronics Society West Japan Joint Chapter 研究会予稿集, pp.43-46 ,口頭発表,下関, 2016 年 1 月
Y. Yamamoto, R. Tsunedomi , Y. Fujita, Y. Kawai, H. Matsumoto, Y. Hamamoto, S. Hazama, H. Nagano, and H. Matsuyama: Pharmacogenetic AUC model can predict efficacy from neoadjuvant axitinib in advanced renal cell carcinoma, The 76th Annual Meeting of the Japanese Cancer Association, Yokohama, Sep. 2017