Artificial intelligence predicts the progression of diabetic kidney disease using big data machine learning von Makino, Masaki, Yoshimoto, Ryo, Ono, Masaki, Itoko, Toshinari, Katsuki, Takayuki, Koseki, Akira, Kudo, Michiharu, Haida, Kyoichi, Kuroda, Jun, Yanagiya, Ryosuke, Saitoh, Eiichi, Hoshinaga, Kiyotaka, Yuzawa, Yukio, Suzuki, Atsushi

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Increasing tendency of urine protein is a risk factor for rapid eGFR decline in patients with CKD: A machine learning-based prediction model by using a big database von Inaguma, Daijo, Kitagawa, Akimitsu, Yanagiya, Ryosuke, Koseki, Akira, Iwamori, Toshiya, Kudo, Michiharu, Yuzawa, Yukio, Shimosawa, Tatsuo

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Development of a machine learning-based prediction model for extremely rapid decline in estimated glomerular filtration rate in patients with chronic kidney disease: a retrospectiv... von Inaguma, Daijo, Hayashi, Hiroki, Yanagiya, Ryosuke, Koseki, Akira, Iwamori, Toshiya, Kudo, Michiharu, Fukuma, Shingo, Yuzawa, Yukio

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A Machine Learning-Based Prediction Model for Trajectory of GFR in CKD Patients with Rapid Decline of GFR by Using a Big Database: PO0529 von Inaguma, Daijo, Kitagawa, Akimitsu, Yanagiya, Ryosuke, Koseki, Akira, Iwamori, Toshiya, Kudo, Michiharu, Fukuma, Shingo, Tsuboi, Naotake, Yuzawa, Yukio

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1040-P: Survival Models of Diabetes Complications Applied to Different Cohorts von KOSEKI, AKIRA, TOKUMASU, REITARO, CHAKRABORTY, PRITHWISH, GHALWASH, MOHAMED, IWAMORI, TOSHIYA, KUDO, MICHIHARU, SOW, DABY, YANAGISAWA, HIROKI, YANAGIYA, RYOSUKE, MAKINO, MASAKI, SUZUKI, ATSUSHI

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Artificial Intelligence Predicts Progress of Diabetic Kidney Disease-Novel Prediction Model Construction with Big Data Machine Learning von MAKINO, MASAKI, ONO, MASAKI, ITOKO, TOSHINARI, KATSUKI, TAKAYUKI, KOSEKI, AKIRA, KUDO, MICHIHARU, HAIDA, KYOICHI, KURODA, JUN, YANAGIYA, RYOSUKE, SUZUKI, ATSUSHI

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924-P: Pattern Mining of Trajectories of Glucose Values of Continuous Glucose Monitoring System by Artificial Intelligence in Type 2 Diabetes Patients von MAKINO, MASAKI, YOSHIMOTO, RYO, KONDO-ANDO, MIZUHO, YOSHINO, YASUMASA, HIRATSUKA, IZUMI, MAKI, WAKAKO, SEKIGUCHI-UEDA, SAHOKO, KAKITA, AYAKO, SHIBATA, MEGUMI, SEINO, YUSUKE, TAKAYANAGI, TAKESHI, ONO, MASAKI, KOSEKI, AKIRA, KUDO, MICHIHARU, HAIDA, KYOICHI, YANAGIYA, RYOSUKE, HAYAKAWA, NOBUKI, SUZUKI, ATSUSHI

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Increasing tendency of urine protein is a risk factor for rapid eGFR decline in patients with CKD: A machine learning-based prediction model by using a big database von Daijo Inaguma, Akimitsu Kitagawa, Ryosuke Yanagiya, Akira Koseki, Toshiya Iwamori, Michiharu Kudo, Yukio Yuzawa, Tatsuo Shimosawa

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Cumulative Stay-time Representation for Electronic Health Records in Medical Event Time Prediction von Katsuki, Takayuki, Miyaguchi, Kohei, Koseki, Akira, Iwamori, Toshiya, Yanagiya, Ryosuke, Suzuki, Atsushi

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Rapid imaging of lung cancer using a red fluorescent probe to detect dipeptidyl peptidase 4 and puromycin-sensitive aminopeptidase activities von Kawashima, Shun, Yoshida, Daisuke, Yoshioka, Takafusa, Ogasawara, Akira, Fujita, Kyohhei, Yanagiya, Masahiro, Nagano, Masaaki, Konoeda, Chihiro, Hino, Haruaki, Kitano, Kentaro, Sato, Masaaki, Hino, Rumi, Kojima, Ryosuke, Komatsu, Toru, Kamiya, Mako, Urano, Yasuteru, Nakajima, Jun

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Electrocardiographic R wave amplitude in V6 lead as a predictive marker of cardiac dysfunction in Duchenne muscular dystrophy von Yamamoto, Tetsushi, Nambu, Yoshinori, Bo, Ryosuke, Morichi, Shotaro, Yanagiya, Misato, Matsuo, Masafumi, Awano, Hiroyuki

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Efficient Catalysis of Acidic Montmorillonite on Addition of Silyl Ketene Acetal to Imine von Onaka, Makoto, Ohno, Ryosuke, Yanagiya, Narutoshi, Izumi, Yusuke

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Radioimmunoassay for bovine plasma 4-Androstenedione and result obtained at the time of pregnancy, parturition, and postpartum von TORII, Ryuzo, NAKAMA, Sanenori, YANAGIYA, Genetsu, SHIMIZU, Ryosuke, IMORI, Tatsuo

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