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Hiroshi Koshimizu

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Hypertension Research : Official Journal of the Japanese Society of Hypertension|July 14, 2020
Future possibilities for artificial intelligence in the practical management of hypertensionHiroshi Koshimizu, Ryosuke Kojima, Yasushi Okuno
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference|October 11, 2013
Blood pressure monitor with a position sensor for wrist placement to eliminate hydrostatic pressure effect on blood pressure measurementHironori Sato, Hiroshi Koshimizu, Shingo Yamashita, et al.
International Journal of Medical Informatics|January 20, 2020
Prediction of blood pressure variability using deep neural networksHiroshi Koshimizu, Ryosuke Kojima, Kazuomi Kario, et al.
Hypertension Research : Official Journal of the Japanese Society of Hypertension|January 12, 2024
Recent developments in machine learning modeling methods for hypertension treatmentHirohiko Kohjitani, Hiroshi Koshimizu, Kazuki Nakamura, et al.
Hypertension Research : Official Journal of the Japanese Society of Hypertension|November 7, 2025
Predicting measurement continuity in home blood pressure monitoring using machine learningAsami Matsumoto, Yohei Mineharu, Hirohiko Kohjitani, et al.
Sleep & Breathing = Schlaf & Atmung|June 9, 2026
Development and internal validation of a prediction model for sleep apnea syndrome treated with continuous positive airway pressure based on claims and health checkup data linked to personal health recordsTatsuya Muraki, Tsuyoshi Ueda, Chihiro Hasegawa, et al.
Hypertension Research : Official Journal of the Japanese Society of Hypertension|September 29, 2019
Multiple measurements of the urinary sodium-to-potassium ratio strongly related home hypertension: TMM Cohort StudyMana Kogure, Takumi Hirata, Naoki Nakaya, et al.
Hypertension Research : Official Journal of the Japanese Society of Hypertension|January 19, 2022
Consideration of the reference value and number of measurements of the urinary sodium-to-potassium ratio based on the prevalence of untreated home hypertension: TMM Cohort StudyMana Kogure, Tomohiro Nakamura, Naho Tsuchiya, et al.
Pageof 1

Showing results (1-10 of 8) with videos related to

Sort By:
Pageof 1
Hypertension Research : Official Journal of the Japanese Society of Hypertension|July 14, 2020
Future possibilities for artificial intelligence in the practical management of hypertensionHiroshi Koshimizu, Ryosuke Kojima, Yasushi Okuno
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference|October 11, 2013
Blood pressure monitor with a position sensor for wrist placement to eliminate hydrostatic pressure effect on blood pressure measurementHironori Sato, Hiroshi Koshimizu, Shingo Yamashita, et al.
International Journal of Medical Informatics|January 20, 2020
Prediction of blood pressure variability using deep neural networksHiroshi Koshimizu, Ryosuke Kojima, Kazuomi Kario, et al.
Hypertension Research : Official Journal of the Japanese Society of Hypertension|January 12, 2024
Recent developments in machine learning modeling methods for hypertension treatmentHirohiko Kohjitani, Hiroshi Koshimizu, Kazuki Nakamura, et al.
Hypertension Research : Official Journal of the Japanese Society of Hypertension|November 7, 2025
Predicting measurement continuity in home blood pressure monitoring using machine learningAsami Matsumoto, Yohei Mineharu, Hirohiko Kohjitani, et al.
Sleep & Breathing = Schlaf & Atmung|June 9, 2026
Development and internal validation of a prediction model for sleep apnea syndrome treated with continuous positive airway pressure based on claims and health checkup data linked to personal health recordsTatsuya Muraki, Tsuyoshi Ueda, Chihiro Hasegawa, et al.
Hypertension Research : Official Journal of the Japanese Society of Hypertension|September 29, 2019
Multiple measurements of the urinary sodium-to-potassium ratio strongly related home hypertension: TMM Cohort StudyMana Kogure, Takumi Hirata, Naoki Nakaya, et al.
Hypertension Research : Official Journal of the Japanese Society of Hypertension|January 19, 2022
Consideration of the reference value and number of measurements of the urinary sodium-to-potassium ratio based on the prevalence of untreated home hypertension: TMM Cohort StudyMana Kogure, Tomohiro Nakamura, Naho Tsuchiya, et al.
Pageof 1