default author photo

Motomichi Kosuga

National Center for Child Health and Development

Tokyo

Japan

  • National Center for Child Health and Development

SCHOLARLY PAPERS

2

DOWNLOADS

118

TOTAL CITATIONS

0

Scholarly Papers (2)

Actions:
Email selected abstracts
1.

​Quantification of glycosaminoglycans in dried blood spots, and evaluation of its usefulness as a secondary newborn screening test for mucopolysaccharidosis

Number of pages: 18 Posted: 24 Nov 2025
Wataru Oboshi, Asami Hirakiyama, Masahiro Miura, Hikaru Omachi, Misa Tanaka, Joo-Hyun Seo, Akira Ohtake, Yoshimitsu Osawa, Mika Ishige, Motomichi Kosuga, Takeshi Munenaga, Ohsuke MIGITA, Hiromi Nyuzuki, Hideo Sasai, Tokiko Fukuda, Shinichiro Sano, Tetsuya Ito, Ryosuke Bo, Yasuhiro Takeshima, Hiroyuki Esaki, Takahito Inoue, Shinichiro Nagamitsu, Yoriko Watanabe, Kimitoshi Nakamura, Hirotake Sawada, Shinsuke Maruyama, Kei Murayama and Torayuki Okuyama
affiliation not provided to SSRN, affiliation not provided to SSRN, affiliation not provided to SSRN, affiliation not provided to SSRN, Saitama University - Saitama Medical University, Saitama University - Saitama Medical University, Saitama Medical University, affiliation not provided to SSRN, affiliation not provided to SSRN, National Center for Child Health and Development, affiliation not provided to SSRN, University of Tsukuba - Department of Child Health, Niigata University - Graduate School of Medical and Dental Sciences, affiliation not provided to SSRN, affiliation not provided to SSRN, affiliation not provided to SSRN, Fujita Health University, affiliation not provided to SSRN, Hyogo Medical University, Sasebo City General Hospital, Fukuoka University, affiliation not provided to SSRN, affiliation not provided to SSRN, Kumamoto University, University of Miyazaki, Kagoshima University, affiliation not provided to SSRN and Saitama University - Saitama Medical University
Downloads 65 (924,743)

Abstract:

Loading...

dermatan sulfate, glycosaminoglycan, Heparan sulfate, keratan sulfate, Mucopolysaccharidosis, newborn screening

2.

Automated Urinary Sediment Detection for Fabry Disease Using Deep-Learning Algorithms

Number of pages: 23 Posted: 14 Jun 2022
Hidetaka Uryu, Ohsuke MIGITA, Minami Ozawa, Chieko Kamijo, Saki Aoto, Kohji Okamura, Fuyuki Hasegawa, Torayuki Okuyama, Motomichi Kosuga and Kenichiro Hata
University of Texas at Houston - Department of Leukemia, University of Tsukuba - Department of Child Health, St. Marianna University School of Medicine, St. Marianna University, National Center for Child Health and Development, National Center for Child Health and Development, National Center for Child Health and Development, National Center for Child Health and Development, National Center for Child Health and Development and National Center for Child Health and Development - Department of Maternal-Fetal Biology
Downloads 53 (1,041,696)

Abstract:

Loading...

Fabry disease, artificial intelligence, deep learning, image augmentation, mulberry cells