Details of the Researcher

PHOTO

Junya Iwazaki
Section
Graduate School of Medicine
Job title
Senior Assistant Professor
Degree

Research History 8

  • 2026/04 - Present
    Tohoku University

  • 2025/04 - 2026/03
    RIKEN

  • 2020/10 - 2025/03
    創生応用医学研究センター　人工知能医学教育基盤コアセンター　AI医学基盤部門

  • 2020/05 - 2025/03
    Tohoku University　Graduate School of Medicine Office of Medical Education

  • 2019/10 - 2025/03
    Tohoku University

  • 2014/04 - 2020/04
    Tohoku University　Graduate School of Medicine Office of Medical Education

  • 2018/10 - 2019/03
    Tohoku University　Center for Information Technology in Education

  • 2013/10 - 2014/03
    Tohoku University　Graduate School of Medicine Office of Medical Education

Show all Show first 5

Professional Memberships 2

  • 日本メディカルAI学会

    2020/10 - Present

  • THE JAPAN SOCIETY FOR MEDICAL EDUCATION

    2015/04 - 2025/03

Research Interests 4

  • 人工知能

  • Medical Education

  • computational complexity theory

  • Information Security

Research Areas 4

  • Informatics / Intelligent informatics /

  • Life sciences / Healthcare management, medical sociology /

  • Informatics / Information security /

  • Informatics / Information theory /

Papers 21

  1. Development and validation of a machine learning model for predicting positive blood cultures using vital signs in ICU patients. International-journal

    Issei Seike, Hiroaki Baba, Shinya Sonobe, Junya Iwazaki, Makoto Miyauchi, Tomoya Kobayashi, Eichi Takaya, Saori Ikumi, Taro Miyamoto, Shota Kawamoto, Shintaro Oyama, Takahiro Imaizumi, Akemi Morohashi, Kengo Oshima, Asami Nakayama, Tetsuji Aoyagi

    Scientific reports　2026/04/24

    DOI： 10.1038/s41598-026-50400-w 　

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    Bloodstream infections require timely and appropriate diagnosis and treatment, as inadequate management is associated with higher mortality. Previous predictive models for bloodstream infection have generally incorporated laboratory test results in addition to vital signs, although laboratory results are not always immediately available in clinical practice. This study aimed to develop and validate a machine learning model to predict positive blood cultures using only vital signs in febrile intensive care unit (ICU) patients (maximum BT ≥ 38 °C). Clinical data from ICU patients at two university hospitals were included, with 597 blood cultures used for model development and 366 for external validation. Six explanatory variables derived from body temperature, heart rate, and mean arterial pressure measured over three days were used to construct a Balanced Random Forest model. The area under the receiver operating characteristic curve was 0.700 ± 0.072 for internal validation and 0.679 ± 0.010 for external validation. SHapley Additive exPlanations value analysis indicated that a larger temperature range contributed to positive predictions, while no increase in temperature, increases in blood pressure, and a decrease in heart rate contributed to negative predictions. The model demonstrates moderate predictive performance and shows comparable results across different datasets. It can continuously monitor the need for blood cultures, thereby serving as an adjunctive tool to support clinical decision-making.

  2. Corrigendum to 'Osteoporosis prediction from frontal lumbar spine X-rays' [Journal of clinical densitometry, volume 29 (2026), 101666]. International-journal

    Ryusei Inamori, Tomoya Kobayashi, Eichi Takaya, Junya Iwazaki, Carlos Makoto Miyauchi, Saori Ikumi, Yoshikazu Okamoto, Cheng Wei Lin, Sheng Che Hsiao, Qingzong Tseng, Shinya Sonobe

    Journal of clinical densitometry : the official journal of the International Society for Clinical Densitometry　101671-101671　2026/01/31

    DOI： 10.1016/j.jocd.2026.101671 　

  3. Osteoporosis prediction from Frontal Lumbar Spine X-rays. International-journal

    Ryusei Inamori, Tomoya Kobayashi, Eichi Takaya, Junya Iwazaki, Carlos Makoto Miyauchi, Saori Ikumi, Yoshikazu Okamoto, Cheng Wei Lin, Sheng Che Hsiao, Qingzong Tseng, Shinya Sonobe

    Journal of clinical densitometry : the official journal of the International Society for Clinical Densitometry　29　(1)　101666-101666　2026

    DOI： 10.1016/j.jocd.2025.101666 　

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    BACKGROUND: This study aimed to evaluate the performance of DeepXray™ Spina, a software that estimates bone mineral density (BMD) and T-scores from frontal lumbar spine X-ray (FLS-X), in predicting osteoporosis. METHODOLOGY: Patients from a Japanese cohort who underwent both FLS-X and dual-energy X-ray absorptiometry (DXA) using Hologic systems within 30 days at Tohoku University Hospital (May 2014-April 2024) were included. BMD was estimated from FLS-X using DeepXray™ Spina, which was developed using dataset from a Taiwanese Cohort. BMD assessed by DXA (observed BMD) and BMD estimated from FLS-X by DeepXray™ Spina (estimated BMD) were compared using Pearson's correlation coefficient (PCC) and normalized root mean square error (NRMSE). T-scores were converted to osteoporosis classifications as normal, osteopenia, or osteoporosis following the World Health Organization criteria. Classification performance was evaluated by accuracy, sensitivity, specificity, Cohen's kappa, and quadratic-weighted Cohen's kappa. RESULTS: The correlation between estimated and observed BMD was strong, with a PCC of 0.901 and an NRMSE of 0.070. For osteoporosis classification, the accuracy, sensitivity, specificity, and Cohen's kappa were as follows: 0.902, 1.000, 0.842, and 0.803 for normal; 0.854, 0.729, 0.924, and 0.673 for osteopenia; 0.951, 0.810, 1.000, and 0.863 for osteoporosis. The quadratic-weighted Cohen's kappa was 0.884. CONCLUSION: This study evaluated the performance of Deep Xray™ Spina in predicting osteoporosis from FLS-X. The software is a practical and reliable tool for predicting osteoporosis, with high performance and robustness.

  4. Clinically informed intermediate reasoning enables generalizable prostate cancer prognostication through machine learning in limited settings. International-journal

    Jun Akatsuka, Kotaro Tsutsumi, Mami Takadate, Yasushi Numata, Hiromu Morikawa, Atsushi Marugame, Hayato Takeda, Yuki Endo, Yuka Toyama, Takayuki Takahashi, Kaori Ono, Junya Iwazaki, Ryuji Ohashi, Akira Shimizu, Tomoharu Kiyuna, Maki Ogura, Masao Ueki, Takuma Kato, Toshiyuki China, Mikio Sugimoto, Hisamitsu Ide, Naoto Sassa, Naonori Ueda, Shigeo Horie, Toyonori Tsuzuki, Go Kimura, Yukihiro Kondo, Yoichiro Yamamoto

    NPJ digital medicine　2025/12/03

    DOI： 10.1038/s41746-025-02193-x 　

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    Machine learning has shown promise in medical image classification. However, its generalizability remains challenging. Here, we show that data-efficient pre-surgical prognostication of prostate cancer from biopsy specimens is enabled by versatile feature extraction from whole-mount histopathology and a clinically informed intermediate reasoning step. With data from multiple institutions, our pipeline resolved dual-domain shifts across specimen types and institutions and achieved consistent external validation, reinforced by comprehensive analyses of generalizability. This highlights the robustness of our prognostic approach when compared to the Gleason grading system. We establish an equitable, interpretable, and clinically applicable framework, supporting actionable decisions for prognosis and treatment planning, even in limited real-world clinical environments.

  5. Operative Time Prediction by Machine Learning for Robot-Assisted Laparoscopic Radical Prostatectomy. International-journal

    Yu Suzuki, Shinya Sonobe, Yoshihide Kawasaki, Saori Ikumi, Eichi Takaya, Carlos Makoto Miyauchi, Tomoya Kobayashi, Junya Iwazaki, Hisanobu Adachi, Naoki Kawamorita, Akihiro Ito

    International journal of urology : official journal of the Japanese Urological Association　2025/11/30

    DOI： 10.1111/iju.70292 　

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    OBJECTIVES: Operative time prediction is crucial for efficient operating room scheduling. This study developed and validated an operative time prediction system for robot-assisted laparoscopic radical prostatectomy using data from two institutions. METHODS: Retrospectively identified 557 and 150 patients who underwent RARP at Tohoku University Hospital and Miyagi Cancer Center were analyzed. The following variables were collected as explanatory variables for the prediction system: Age, height, body mass index, comorbidities, performance status, prostate volume, tumor extent of local invasion, grade group, prostatitis, preoperative treatment, history of intraperitoneal surgery, lymphadenectomy, and nerve-sparing. In addition, the observed operative time was collected as a source variable for the objective variable. The observed operative time was calculated as the sum of components related to institutional, operator, and patient factors. Approximation curves were applied to the first two components, while a random forest-based machine learning model was applied to the latter, resulting in the development of an integrated prediction system. RESULTS: The normalized root mean square error between the observed and predicted operative times was 0.107 in internal validation and 0.148 in external validation, demonstrating greater reliability than the expected operative time by operators in advance. Factors that are known to impact operative time, such as lymphadenectomy, grade group, prostate volume, and body mass index, were identified as contributing variables. CONCLUSIONS: The system provides a reliable and robust prediction focusing on factors known to impact operative time. It has the potential to improve the efficiency of operating room scheduling.

  6. 畳み込みニューラルネットワークによる過敏性腸症候群の脳波識別

    村椿 智彦, 金井 貴英, 小松 由弥, 橋目 俊輝, 岩崎 淳也, 相澤 祐一, 鹿野 理子, 金澤 素, 福土 審

    心身医学　64　(3)　281-281　2024/05

    Publisher: (一社)日本心身医学会

    ISSN： 0385-0307

  7. Development and validation of machine learning prediction model for post-rehabilitation functional outcome after intracerebral hemorrhage

    Shinya Sonobe, Tetsuo Ishikawa, Kuniyasu Niizuma, Eiryo Kawakami, Takuya Ueda, Eichi Takaya, Carlos Makoto Miyauchi, Junya Iwazaki, Ryuzaburo Kochi, Toshiki Endo, Arun Shastry, Vijayananda Jagannatha, Ajay Seth, Atsuhiro Nakagawa, Masahiro Yoshida, Teiji Tominaga

    Interdisciplinary Neurosurgery　29　101560-101560　2022/09

    DOI： 10.1016/j.inat.2022.101560 　

    ISSN： 2214-7519

    eISSN： 2214-7519

  8. A Construction of Cramer-Shoup Like Encryption Protocols Based on the Anshel-Anshel-Goldfeld Key Exchange Protocol Peer-reviewed

    Shuji Isobe, Jun-ya Iwazaki, Eisuke Koizumi, Atsushi Suda

    The Sixth International Symposium on Computing and Networking Workshops (CANDAR 2018)　410-416　2018

    Publisher: IEEE Computer Society

    DOI： 10.1109/CANDARW.2018.00082 　

  9. A Method for Constructing an Autonomous Decentralized P2P Storage with High Confidentiality and Reliability Peer-reviewed

    Masayuki Fukumitsu, Shingo Hasegawa, Shuji Isobe, Jun-ya Iwazaki, Eisuke Koizumi, Masao Sakai

    4th International Workshop on Information and Communication Security (WICS`17)　439-444　2017/11

    Publisher: IEEE Computer Society

    DOI： 10.1109/CANDAR.2017.67 　

  10. Blockchain: Towards Secure Data Linkage Among Medical Institutions in Distributed and Autonomous Manner

    Transactions of Japanese Society for Medical and Biological Engineering　55　(3)　227-227　2017

    Publisher: Japanese Society for Medical and Biological Engineering

    DOI： 10.11239/jsmbe.55Annual.227 　

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    <p>With the development of the big data and artificial intelligence technologies, it is expected that huge patient medical data will be used for medical progress such as computer-aided detection/diagnosis. However, it is not easy to build a system for aggregating medial data from many institutions and utilizing them each other as the conventional central management system. The accumulated data volume is huge, and high-level security is needed for its protection. Complicated access control is also required since the security setting of each individual data varies depending on its ownership and permission policy. On the other hand, autonomous decentralized systems using Blockchain technology such as Bitcoin have gained attention. The novel technology can be expected to overcome such difficulties caused by the conventional central management system. In the presentation, a method to realize secure data linkage among medical institutions with the Blockchain technology will be discussed.</p>

  11. A Proposal of a Secure P2P-type Storage Scheme by using the Secret Sharing and the Blockchain Peer-reviewed

    Masayuki Fukumitsu, Shingo Hasegawa, Jun-Ya Iwazaki, Masao Sakai, Daiki Takahashi

    2017 IEEE 31ST INTERNATIONAL CONFERENCE ON ADVANCED INFORMATION NETWORKING AND APPLICATIONS (AINA)　803-810　2017

    DOI： 10.1109/AINA.2017.11 　

    ISSN： 1550-445X

  12. Number of papers published in English from the nursing departments of 42 national universities in Japan in the past ten years Peer-reviewed

    Junichi Kameoka, Junya Iwazaki, Fumie Takahashi, Fumiko Sato, Kazuki Sato, Atsuko Taguchi, Yasuka Nakamura, Seiichi Ishii, Yutaka Kagaya

    NURSE EDUCATION TODAY　38　138-143　2016/03

    DOI： 10.1016/j.nedt.2015.11.028 　

    ISSN： 0260-6917

    eISSN： 1532-2793

  13. A proposal of a password manager satisfying security and usability by using the secret sharing and a personal server Peer-reviewed

    Masayuki Fukumitsu, Shingo Hasegawa, Jun-ya Iwazaki, Masao Sakai, Daiki Takahashi

    IEEE 30TH INTERNATIONAL CONFERENCE ON ADVANCED INFORMATION NETWORKING AND APPLICATIONS IEEE AINA 2016　661-668　2016

    DOI： 10.1109/AINA.2016.45 　

    ISSN： 1550-445X

  14. A Rigorous Security Proof for the Enhanced Version of Password-Protected Secret Sharing Scheme Peer-reviewed

    HASEGAWA Shingo, ISOBE Shuji, IWAZAKI Jun-ya, KOIZUMI Eisuke, SHIZUYA Hiroki

    IIS　22　(1)　31-55　2016

    Publisher: 東北大学大学院情報科学研究科ジャーナル編集委員会

    DOI： 10.4036/iis.2015.R.04 　

    ISSN： 1340-9050

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    The password-protected secret sharing (PPSS, for short) and its security notion, called in this paper the PPSS-security, were proposed by Bagherzandi, Jarecki, Saxena and Lu. However, another security notion for PPSS schemes, the pparam-security was proposed by Hasegawa, Isobe, Iwazaki, Koizumi and Shizuya, because they pointed out an attack which can break the original protocol proposed by Bagherzandi &lt;i&gt;et al.&lt;/i&gt; Hasegawa &lt;i&gt;et al.&lt;/i&gt; also showed how to enhance the protocol, and proved that the enhanced one is pparam-secure. In this paper, we prove that the enhanced one is PPSS-secure as well.

  15. Scienceの"Editors'Choice"定期配信によるリサーチマインド・俯瞰力・英語力養成

    亀岡 淳一, 岩崎 淳也, 高橋 文恵, 荒田 悠太郎, 加賀谷 豊

    医学教育　46　(Suppl.)　200-200　2015/07

    Publisher: (一社)日本医学教育学会

    ISSN： 0386-9644

  16. 医学科学生の外科志望に及ぼす卒前教育の影響の質的研究 Peer-reviewed

    石井誠一, 亀岡淳一, 加賀谷, 岩﨑淳也, 荒田悠太郎, 高橋文恵

    医学教育　46supple　(Suppl.)　153-153　2015/07/01

    Publisher:

    ISSN： 0386-9644

  17. よくある症状から患者さんへのアプローチの仕方を学ぼう−医学科１年生の新しい融合型PBLカリキュラム導入− Peer-reviewed

    石井誠一, 亀岡淳一, 加賀谷 豊, 岩﨑淳也, 高橋文恵, 荒田悠太郎

    東北大学高度教養教育・学生支援機構紀要　1　(1)　201-206　2015/03/01

    Publisher:

    ISSN： 2189-5945

  18. A strengthened security notion for password-protected secret sharing schemes Peer-reviewed

    Shingo Hasegawa, Shuji Isobe, Jun-Ya Iwazaki, Eisuke Koizumi, Hiroki Shizuya

    IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences　E98A　(1)　203-212　2015/01/01

    Publisher: Maruzen Co., Ltd.

    DOI： 10.1587/transfun.E98.A.203 　

    ISSN： 1745-1337 0916-8508

  19. Password-protected Secret-sharing Schemes without Random Oracles Peer-reviewed

    Shingo Hasegawa, Shuji Isobe, Jun-ya Iwazaki, Eisuke Koizumi, Hiroki Shizuya

    2014 INTERNATIONAL SYMPOSIUM ON INFORMATION THEORY AND ITS APPLICATIONS (ISITA)　566-570　2014

  20. On the Little Knowledge Interactive Proof Peer-reviewed

    IWAZAKI Jun-ya, HASEGAWA Shingo, ISOBE Shuji, KOIZUMI Eisuke, SHIZUYA Hiroki

    Technical report of IEICE. ISEC　111　(285)　149-154　2011/11

    Publisher: 一般社団法人電子情報通信学会

    ISSN： 0913-5685

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    We propose the notion of little knowledgeness in interactive proof systems, as a notion alternative to the zero knowledgeness, which means that no verifier can obtain any advice to extract the prover&#039;s secret from the conversation history. We show that, under some conditions, functions that have computational zero knowledge interactive proofs also have little knowledge interactive proofs.

  21. On the Little Knowledge Interactive Proof Peer-reviewed

    IWAZAKI Jun-ya, HASEGAWA Shingo, ISOBE Shuji, KOIZUMI Eisuke, SHIZUYA Hiroki

    電子情報通信学会技術研究報告. LOIS, ライフインテリジェンスとオフィス情報システム = IEICE technical report. LOIS, Life intelligence and office information systems　111　(286)　149-154　2011/11

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Misc. 5

  1. 臨床実習ローテート科と卒業後進路の関係 過去35年間の東北大学卒業生へのアンケートより

    亀岡 浩一, 岩崎 淳也, 内海 衣恵, 石井 直人, 石井 誠一, 加賀谷 豊

    医学教育　48　(Suppl.)　105-105　2017/08

    Publisher: (一社)日本医学教育学会

    ISSN： 0386-9644

  2. アウトカム評価としての診療録ピアレビューシステムの基準連関妥当性の検討

    亀岡 淳一, 大久保 智哉, 菊川 誠, 岩崎 淳也, 佐藤 佐織, 石井 誠一, 加賀谷 豊

    医学教育　47　(Suppl.)　208-208　2016/07

    Publisher: (一社)日本医学教育学会

    ISSN： 0386-9644

  3. 基礎研究医育成 文部科学省GPプログラムの検証

    石井 誠一, 加賀谷 豊, 亀岡 淳一, 岩崎 淳也, 荒田 悠太郎

    医学教育　46　(Suppl.)　123-123　2015/07

    Publisher: (一社)日本医学教育学会

    ISSN： 0386-9644

  4. 臨床実習後OSCEで身体診察による臨床推論力を測定できるか

    亀岡 淳一, 荒田 悠太郎, 岩崎 淳也, 石井 誠一, 加賀谷 豊

    医学教育　46　(Suppl.)　124-124　2015/07

    Publisher: (一社)日本医学教育学会

    ISSN： 0386-9644

  5. A-7-4 An Evaluation of a Password Manager by using the Secret Sharing, a Personal Server and a Smartphone in the UDS Framework

    Fukumitsu Masayuki, Hasegawa Shingo, Iwazaki Junya, Sakai Masao, Takahashi Daiki

    Proceedings of the IEICE General Conference　2015　138-138　2015/02/24

    Publisher: The Institute of Electronics, Information and Communication Engineers

Books and Other Publications 1

  1. 【医療AIの普及拡大とさらなる展開 医療からヘルスケアサービスまで発展に向けた現状と展望】医療AIのための人材育成の現状と展望 東北大学Clinical AIの歩みと今後の展望

    岩崎 淳也

    (株)インナービジョン　2023/06

    ISBN: 9784910561301

Presentations 18

  1. 自然言語処理に基づく診療録仮名化データセットの構築

    髙屋英知, 岩﨑淳也, 宮内誠, 小林智哉, 園部真也

    第6回 日本メディカルAI学会学術集会　2024/06/21

  2. 診療録のテキスト類似性計算手法の探索：電子カルテデータの横断的利用に向けた研究

    宮内誠, 髙屋英知, 岩﨑淳也, 小林智哉, 園部真也

    第6回 日本メディカルAI学会学術集会　2024/06/21

  3. 24 万人分の診療録を用いた 日本語版医療用大規模言語モデル構築の試み

    岩﨑淳也, 髙屋英知, 宮内誠, 小林智哉, 園部真也

    第6回 日本メディカルAI学会学術集会　2024/06/21

  4. 医療AI教育の実践と一考察

    岩崎淳也, 田宮元, 植田琢也, 園部真也, 本間経康, 宮内誠カルロス, 高屋英知

    第55回日本医学教育学会大会　2023/07/28

  5. Long short-term memory による過敏性腸症候群の脳波識別

    村椿智彦, 清水悠生, 成田魁, 持田尚人, 岩崎淳也, 相澤祐一, 金澤素, 福土審

    第63回日本心身医学会総会ならびに学術講演会　2022/06/25

  6. 脳波を用いた過敏性腸症候群の診断AI

    清水悠生, 成田魁, 持田尚人, 村椿智彦, 岩崎淳也, 相澤祐一, 金澤素, 福土審

    第94回日本心身医学会東北地方会　2022/02/25

  7. コロナ禍における医学生のストレスとその解決方法に関する一考察

    岩崎 淳也, 加賀谷 豊, 石井 誠一, 齋木 由利子, 田中 淳一, 石井 直人

    日本医学教育学会　2021/07

  8. A Method for a Practical Smart Contract by using Blockchain and Centralized Server

    福光 正幸, 長谷川 真吾, 磯辺 秀司, 岩田 直樹, 岩崎 淳也, 小泉 英介, 中田 恒夫, 酒井 正夫

    電子情報通信学会技術研究報告 = IEICE technical report : 信学技報　2018/07/25

  9. A Method for Constructing an Autonomous Decentralized P2P Storage with High Confidentiality and Reliability

    Masayuki Fukumitsu, Shingo Hasegawa, Shuji Isobe, Jun Ya Iwazaki, Eisuke Koizumi, Masao Sakai

    Proceedings - 2017 5th International Symposium on Computing and Networking, CANDAR 2017　2018/04/23

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    © 2017 IEEE. We have proposed a decentralized Peer-to-Peer (P2P) cloud storage scheme achieving high confidentiality by using a large number of unspecified P2P nodes. There is one crucial problem in the scheme: it is generally difficult to maintain the reliability of the stored data since there is no designated central server which supervises the whole system, and hence, it will be infeasible to certainly restore the stored data if the P2P nodes are to be less reliable. In this paper, we propose a method to maintain the high reliability of the stored data by applying mutual monitoring and autonomous recovering operations among the P2P nodes. Using the method in combination with the conventional scheme, one can achieve a high reliability P2P cloud storage with high confidentiality. We then give a quantitative evaluation of the reliability on the stored data in the proposed storage.

  10. A proposal of a secure P2P-type storage scheme by using the secret sharing and the blockchain

    Masayuki Fukumitsu, Shingo Hasegawa, Junya Iwazaki, Masao Sakai, Daiki Takahashi

    Proceedings - International Conference on Advanced Information Networking and Applications, AINA　2017/05/05

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    © 2017 IEEE. We propose a new secure online storage scheme based on an open P2P network without a central server. In the proposed scheme, attackers cannot detect target user data in the online storage because the user data is divided into some parts by the secret sharing, and they are distributed to P2P nodes via the anonymous communication. The proposed scheme can prevent the direct attack on the target user node because metadata for the reconstruction also hidden in the online storage, hence nothing remains in the user node. Even if the state of the P2P network varies over time between the storing and restoring operation, the proposed scheme ensures that the user can identify the target nodes which stored his metadata by utilizing the Blockchain technology with only memorable secure information for user authentication. Furthermore, a malicious node to attack on others can be detected and ruled out by the mutual monitoring among the nodes and the majority decision rule.

  11. Blockchain: Towards Secure Data Linkage Among Medical Institutions in Distributed and Autonomous Manner

    岩崎 淳也, 酒井 正夫

    Trans. jpn. Soc. Med. Bio. Eng　2017

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    <p>With the development of the big data and artificial intelligence technologies, it is expected that huge patient medical data will be used for medical progress such as computer-aided detection/diagnosis. However, it is not easy to build a system for aggregating medial data from many institutions and utilizing them each other as the conventional central management system. The accumulated data volume is huge, and high-level security is needed for its protection. Complicated access control is also required since the security setting of each individual data varies depending on its ownership and permission policy. On the other hand, autonomous decentralized systems using Blockchain technology such as Bitcoin have gained attention. The novel technology can be expected to overcome such difficulties caused by the conventional central management system. In the presentation, a method to realize secure data linkage among medical institutions with the Blockchain technology will be discussed.</p>

  12. アウトカム評価としての診療録ピアレビューシステムの基準連関妥当性の検討

    亀岡 淳一, 大久保 智哉, 菊川 誠, 岩崎 淳也, 佐藤 佐織, 石井 誠一, 加賀谷 豊

    医学教育　2016/07

  13. A proposal of a password manager satisfying security and usability by using the secret sharing and a personal server

    Masayuki Fukumitsu, Shingo Hasegawa, Jun Ya Iwazaki, Masao Sakai, Daiki Takahashi

    Proceedings - International Conference on Advanced Information Networking and Applications, AINA　2016/05/19

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    © 2016 IEEE. Password managers protect users' passwords by using a master password or a security token. The security of them using the master password is weakened if users use weak master passwords. The usability of them using the security token is low since users always need the token to log in. In this paper, we propose a new framework of password managers which has a high security and a high usability by employing the secret sharing and a personal servers for a user.

  14. Scienceの"Editors'Choice"定期配信によるリサーチマインド・俯瞰力・英語力養成

    亀岡 淳一, 岩崎 淳也, 高橋 文恵, 荒田 悠太郎, 加賀谷 豊

    医学教育　2015/07

  15. 医学科学生の外科志望に及ぼす卒前教育の影響の質的研究

    石井 誠一, 高橋 文恵, 荒田 悠太郎, 亀岡 淳一, 加賀谷 豊, 岩崎 淳也

    医学教育　2015/07

  16. A-7-4 An Evaluation of a Password Manager by using the Secret Sharing, a Personal Server and a Smartphone in the UDS Framework

    Fukumitsu Masayuki, Hasegawa Shingo, Iwazaki Junya, Sakai Masao, Takahashi Daiki

    Proceedings of the IEICE General Conference　2015/02/24

  17. Learning How to Approach a Patient with Common Symptoms : Introduction of a New PBL Curriculum to First-Year Medical Students

    石井 誠一, 加賀谷 豊, 亀岡 淳一, 岩崎 淳也, 高橋 文恵, 荒田 悠太郎

    東北大学高度教養教育・学生支援機構紀要 = Bulletin of the Institute for Excellence in Higher Education, Tohoku University　2015

  18. A Proposal of a Password Manager Satisfying Security and Usability by Using the Secret Sharing and a Personal Server.

    福光 正幸, 長谷川 真吾, 岩崎 淳也, 酒井 正夫, 高橋 大樹

    コンピュータセキュリティシンポジウム2014論文集　2014/10/15

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Industrial Property Rights 8

  1. 情報処理システム、情報処理装置、情報処理方法、及び、プログラム

    長谷川 真吾, 岩崎 淳也, 酒井 正夫, 高橋 大樹, 福光 正幸

    Property Type: Patent

  2. 情報処理装置、管理装置、不正モジュール検知システム、不正モジュール検知方法、不正モジュール検知プログラムを記録している記録媒体、管理方法、管理プログラムを記録している記録媒体および集積回路

    海上 勇二, 布田 裕一, 松崎 なつめ, 静谷 啓樹, 酒井 正夫, 磯辺 秀司, 小泉 英介, 長谷川 真吾, 岩崎 淳也

    Property Type: Patent

  3. 情報処理システム、公開鍵の変更方法、および、プログラム

    酒井正夫, 岩崎淳也, 小泉英介, 長谷川真吾, 磯邉秀司, 福光正幸

    Property Type: Patent

  4. 情報処理システム、データ提供方法、および情報処理システムの製造方法

    酒井正夫, 岩崎淳也, 小泉英介, 長谷川真吾, 磯邉秀司, 福光正幸

    Property Type: Patent

  5. 情報仲介装置、情報提供装置、及び情報取得装置

    酒井正夫, 中田恒夫, 岩田直樹, 福光正幸, 長谷川真吾, 磯辺秀司, 岩崎淳也, 小泉英介

    Property Type: Patent

  6. 情報処理装置、管理装置、不正モジュール検知システム、不正モジュール検知方法、不正モジュール検知プログラムを記録している記録媒体、管理方法、管理プログラムを記録している記録媒体および集積回路

    海上 勇二, 布田 裕一, 松崎 なつめ, 静谷 啓樹, 酒井 正夫, 磯辺 秀司, 小泉 英介, 長谷川 真吾, 岩崎 淳也

    特許第5411282号

    Property Type: Patent

  7. サービスデータ提供方法、および情報処理システムの製造方法

    酒井正夫, 岩崎淳也, 小泉英介, 久井雅史

    Property Type: Patent

  8. 情報処理システム、情報処理装置、情報処理方法、及び、プログラム

    長谷川真吾, 岩崎淳也, 酒井正夫, 高橋大樹, 福光正幸

    Property Type: Patent

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    PCT/JP2016/80351

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Research Projects 3

  1. 全国の電子カルテ情報の統合データベース作成を可能にする自然言語処理技術の開発

    岩崎 淳也, 園部 真也, 高屋 英知, 宮内 誠

    Offer Organization: 日本学術振興会

    System: 科学研究費助成事業

    Category: 基盤研究(C)

    Institution: 国立研究開発法人理化学研究所

    2025/04/01 - 2028/03/31

  2. The development of new undergraduate medical education program designed to cultivate medical professionals capable of solving healthcare challenges through AI.

    Iwazaki Junya

    Offer Organization: Japan Society for the Promotion of Science

    System: Grants-in-Aid for Scientific Research

    Category: Grant-in-Aid for Early-Career Scientists

    Institution: Tohoku University

    2021/04/01 - 2024/03/31

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    Healthcare challenges existing within the Graduate School of Medicine at Tohoku University and its affiliated institutions were identified, and based on these challenges, a specialized medical AI educational program for healthcare professionals was developed. By the end of March 2023, 294 medical practitioners had enrolled in the program, of which 59 (approximately 20.0%) completed it. Among the completers were doctoral students (physicians) from the Graduate School of Medicine at Tohoku University who, as of July 2023, had one AI-related paper accepted for publication and received eight awards for oral presentations and similar recognitions. Additionally, medical students made two oral presentations. Therefore, the educational program proposed in this study is suggested to be effective for medical practitioners.

  3. Development of a privacy-preserving infectious disease control platform using distributed signature technology to continue healthy social activities in the new normal era

    Junya Iwazaki

    2021/04 - 2021/09