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Studies in Health Technology and Informatics|June 24, 2020
Interpretation Method for Continuous Glucose Monitoring with Subsequence Time-Series ClusteringMasaki Ono, Takayuki Katsuki, Masaki Makino, et al.
Studies in Health Technology and Informatics|June 24, 2020
Feature Set for a Prediction Model of Diabetic Kidney Disease ProgressionMasaki Ono, Takayuki Katsuki, Masaki Makino, et al.
Scientific Reports|November 21, 2022
Machine learning models for prediction of HF and CKD development in early-stage type 2 diabetes patientsEiichiro Kanda, Atsushi Suzuki, Masaki Makino, et al.
Endocrine Journal|September 25, 2015
Simultaneous measurement of serum chemokines in autoimmune thyroid diseases: possible role of IP-10 in the inflammatory responseIzumi Hiratsuka, Mitsuyasu Itoh, Hiroya Yamada, et al.
The Journal of Clinical Endocrinology and Metabolism|January 10, 2003
Genetic variations in calpain-10 gene are not a major factor in the occurrence of type 2 diabetes in JapaneseYukio Horikawa, Naohisa Oda, Li Yu, et al.
Thyroid : Official Journal of the American Thyroid Association|April 20, 2012
Relative levels of the inflammatory cytokine TNFα and the soluble CD40 ligand profile in serum correlate with the thyrotoxic activity of Graves' diseaseKeiko Yamamoto, Mitsuyasu Itoh, Tomoko Okamura, et al.
Studies in Health Technology and Informatics|April 22, 2018
Risk Prediction of Diabetic Nephropathy via Interpretable Feature Extraction from EHR Using Convolutional AutoencoderTakayuki Katsuki, Masaki Ono, Akira Koseki, et al.
Experimental and Clinical Endocrinology & Diabetes : Official Journal, German Society of Endocrinology [And] German Diabetes Association|September 21, 2018
Changes in Serum Immunoglobulin G4 Levels in Patients with Newly Diagnosed Graves' DiseaseIzumi Hiratsuka, Hiroya Yamada, Mitsuyasu Itoh, et al.
Scientific Reports|August 16, 2019
Artificial intelligence predicts the progression of diabetic kidney disease using big data machine learningMasaki Makino, Ryo Yoshimoto, Masaki Ono, et al.
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