CREST [Society 5.0 System Software]
This project is the 2021 JST Strategic Creative Research Promotion Project( CREST) Research area, "Creation of basic software for Society 5.0 by fusing basic theory and system basic technology", Toshio Okabe Director) This is the research project "Anonymous healthcare cohort with the guarantee of data privacy and utility".
We aim to establish next-generation anonymously processed data that is theoretically secure against the threat of re-identification and gives a statistical evaluation of errors that occur during processing. Integrated health diagnosis data, healthcare data, and health insurance clain data are used for lifestyle-related diseases. With a mathematical model that predicts the morbidity of injuries and illnesses, it is possible to improve the lives of insured persons, create health strategies in the government, and develop pharmaceutical products at an early stage. |
Group name th> | Principal or Principal Name of collaborator th> | Principal or Principal Collaborator's institution / department / job title th> | Research subject th> |
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Kikuchi Group td> | Hiroaki Kikuchi td> | Meiji University, Faculty of Comprehensive Mathematics, Professor td> | Research Supervision Differential Privacy Anonymization technology using synthetic medical data td> |
Kanamori Group td> | Sachiko Kanamori td> | National Institute of Information and Communications Technology Cyber Security Research Institute / Director td> | Privacy Enhaced Data Analysis td> |
Arai Group td> | Hiromi Arai td> | RIKEN/ AI Safety and Reliability Unit Unit Leader td> | To develop explanation methods for consent td> |
Mori Group td> | Yukiko Mori td> | Kyoto University Hospital, Lecturer td> | Usefulness of anonymously medical data td> |
Nojima Group td> | Ryo Nojima td> | Ritsumeikan University, Faculty of Informatics, Professor td> | Application of security index of anonymization to machine learning td> |
Principal Investigator Group Kikuchi Group span> p>
Name of Principal Investigator th>
Affiliation, department th>
Position th>
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Hiroaki Kikuchi td>
Meiji University, Faculty of Comprehensive Mathematics td>
Professor td>
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Names of research participants th>
Affiliation, department (omitted if same as above) th>
Position th>
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Andres Hernandez-Matamoros td>
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Postdoctoral Fellow td>
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Satoshi Ito td>
Faculty of Bussines and Commerce, Aichi Gakuin University td>
Lecturer td>
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Koji Chida td>
Faculty of Informatics, Gunma University td>
Associate Professor td>
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Koki Hamada td>
Nippon Telegraph and Telephone Corporation,NTT Social Informatics Laboratories td>
Associate Special Researcher td>
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Masanobu Kii td>
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Employee td>
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Hideo Yasunaga td>
The University of Tokyo, Graduate School of Medicine, Department of Public Health Medicine td>
Professor td>
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Differential Private process for anonymization p>
As the principal investigator, we supervise all research groups and we are in charge of three tasks.
Challenge 2. Anonymization benchmark using synthetic medical data
Issue 3. Proposal of processing method that guarantees theoretical security against re-identification by differential privacy
Problem 4. Establishment of utility measure that guarantees error range using moment generating function p>
Collaborative Research Group (1) Kanamori Group span> p>
Name of Principal Investigator th>
Affiliation, department th>
Position th>
tr>
Sachiko Kanamori td>
National Institute of Information and Communications Technology Cyber Security Research Institute, Security Infrastructure Laboratory td>
Director td>
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Names of research participants th>
Affiliation, department (omitted if same as above) th>
Position th>
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Le Trieu Phong td>
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Senior Research td>
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Lihua Wang td>
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Senior Research td>
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Tran Thi Phuong
Senior Research
Hajime Ono td>
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Researcher td>
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Privacy-protected data analysis method p>
Proposal of processing method that guarantees theoretical safety against re-identification by differential privacy p>
Collaborative Research Group (2) Arai Group span> p>
Name of Principal Investigator th>
Affiliation, department th>
Position th>
tr>
Hiromi Arai td>
RIKEN Center for Advanced Intelligence Research td>
Unit leader td>
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Names of research participants th>
Affiliation, department (omitted if same as above) th>
Position th>
tr>
Tetsushi Oki td>
Department of Information Science, Faculty of Informatics, Shizuoka University td>
Associate Professor td>
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Tadashi Mima td>
Keio University Graduate School of Media and Governance td>
Project Professor td>
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Sakamoto Taka
Faculty of Informatics, Shizuoka University
Specially Appointed Associate Professor
Development of a sound explanation method for obtaining consent p>
(1) Research on explanation of personal data usage
(2) Development of information presentation method to explain the use of personal data p>
Collaborative Research Group (4) Mori Group span> p>
Name of Principal Investigator th>
Affiliation, department th>
Position th>
tr>
Yukiko Mori td>
Kyoto University Hospital, Medical Information Planning Department td>
Lecturer td>
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Names of research participants th>
Affiliation, department (omitted if same as above) th>
Position th>
tr>
Tomohiro Kuroda td>
Kyoto University Hospital Medical Information Planning Department td>
Professor td>
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Kenichi Saito td>
td>
Specific Assistant Professor td>
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Toshiyuki Inagaki td>
Life Data Initiative, General Incorporated Association td>
Secretary General td>
tr>
Jun Suzumoto
Department of Medical Informatics, Graduate School of Medicine, Kyoto University
Doctoral Program University Students
Keita Fukuyama
Medical Information Planning Department
Teacher Assistant
Roberto Espinoza Chamorro
Graduate School of Informatics, Kyoto University Social Informatics Course, Medical Informatics
Ph.D. Student
Collaborative Research Group (5)Nojima Group
Names of research participants th> | Affiliation, department (omitted if same as above) th> | Position th> |
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Ryo Nojima | Ritsumeikan University, Faculty of Informatics | Professor |
Quality evaluation of anonymously processed information
(1) Verification using actual medical information of anonymous processing by differential privacy
(2) Verification of analysis reproducibility using anonymously processed information p>