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Masaki Makino
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2020 – today
- 2021
- [c6]Mohamed F. Ghalwash, Prithwish Chakraborty, Akira Koseki, Hiroki Yanagisawa, Toshiya Iwamori, Ray Tokumasu, Masaki Makino, Ryosuke Yanagiya, Atsushi Suzuki, Michiharu Kudo, Daby Sow:
A Comparative Time-to-Event Analysis Across Health Systems. AMIA 2021 - 2020
- [c5]Masaki Ono, Takayuki Katsuki, Masaki Makino, Kyoichi Haida, Atsushi Suzuki:
Interpretation Method for Continuous Glucose Monitoring with Subsequence Time-Series Clustering. MIE 2020: 277-281 - [c4]Masaki Ono, Takayuki Katsuki, Masaki Makino, Kyoichi Haida, Atsushi Suzuki, Reitaro Tokumasu:
Feature Set for a Prediction Model of Diabetic Kidney Disease Progression. MIE 2020: 1289-1290
2010 – 2019
- 2018
- [c3]Takayuki Katsuki, Masaki Ono, Akira Koseki, Michiharu Kudo, Kyoichi Haida, Jun Kuroda, Masaki Makino, Ryosuke Yanagiya, Atsushi Suzuki:
Feature Extraction from Electronic Health Records of Diabetic Nephropathy Patients with Convolutioinal Autoencoder. AAAI Workshops 2018: 451-454 - [c2]Takayuki Katsuki, Takayuki Osogami, Akira Koseki, Masaki Ono, Michiharu Kudo, Masaki Makino, Atsushi Suzuki:
Time-Discounting Convolution for Event Sequences with Ambiguous Timestamps. ICDM 2018: 1085-1090 - [c1]Takayuki Katsuki, Masaki Ono, Akira Koseki, Michiharu Kudo, Kyoichi Haida, Jun Kuroda, Masaki Makino, Ryosuke Yanagiya, Atsushi Suzuki:
Risk Prediction of Diabetic Nephropathy via Interpretable Feature Extraction from EHR Using Convolutional Autoencoder. MIE 2018: 106-110 - [i1]Takayuki Katsuki, Takayuki Osogami, Akira Koseki, Masaki Ono, Michiharu Kudo, Masaki Makino, Atsushi Suzuki:
Time-Discounting Convolution for Event Sequences with Ambiguous Timestamps. CoRR abs/1812.02395 (2018)
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