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2021 Fiscal Year Research-status Report

Secure, Precise and Fast Sequential Pattern Mining with Learning Data Distribution

Research Project

Project/Area Number 21K17746
Research InstitutionTokyo Institute of Technology

Principal Investigator

Le Hieu・Hanh  東京工業大学, 情報理工学院, 助教 (60813996)

Project Period (FY) 2021-04-01 – 2024-03-31
Keywordsprivacy / data mining / differential privacy / recommendation
Outline of Annual Research Achievements

This study aims to present a method for eliminating the need for trust in sequential pattern mining (SPM) while preserving privacy and providing secure, precise, and fast sequential data analysis which carefully learns the data distribution.
The fundamental algorithms of sequential data analysis on sequential medical data without privacy-preserving have been studied this year. In detail, utilizing SPM with clustering, the research extracts and compares the clinical pathways from multiple hospitals and discovers the association rules used for specimen inspection recommendations.
These algorithms will be used as base methods for evaluating the effectiveness of the privacy-preserving SPM in the following years.

Current Status of Research Progress
Current Status of Research Progress

3: Progress in research has been slightly delayed.

Reason

Due to the spread of COVID19 and the shortage of semiconductors, the preparation of medical data from multiple hospitals and the delivery of the server were delayed. Therefore, the evaluation of the proposed privacy-preserving analysis algorithm could not be performed on time.

Strategy for Future Research Activity

In the following year, as the experimental environment and the fundamental analyzing methods were already constructed, the privacy-preserving analysis will be evaluated. At the same time, a method to further reduce the mining time will be proposed and evaluated.

Causes of Carryover

Due to the spread of the COVID19 infection, it was not possible to make oeversea and domestic business trips. Therefore, the expenses for travel and conference participation fees were carried over to the next year.

  • Research Products

    (4 results)

All 2022 2021

All Presentation (4 results) (of which Int'l Joint Research: 1 results)

  • [Presentation] MERJ: Medical Entity-Relation Extraction System for Japanese Clinical Texts2022

    • Author(s)
      An Wang, Hieu Hanh Le, Ryosuke Matsuo, Tomoyoshi Yamazaki, Kenji Araki, Haruo Yokota
    • Organizer
      The 14th Forum on Data Engineering and Information Management (DEIM 202)
  • [Presentation] シーケンシャルパターンマイニングに基づく多病院間の頻出治療パターンの比較2022

    • Author(s)
      Li Yuqing, Le Hieu Hanh, 松尾亮輔, 山崎友義, 荒木賢二, 横田治夫
    • Organizer
      第14回データ工学と情報マネジメントに関するフォーラム予稿集
  • [Presentation] 医療データのシーケンス解析とその課題2022

    • Author(s)
      横田治夫, Le Hieu Hanh, 松尾亮輔, 山﨑友義, 荒木賢二
    • Organizer
      第12回日本医療情報学会「医用人工知能研究会」人工知能学会「医用人工知能研究会」合同研究会
  • [Presentation] Sequential Pattern Mining of Large Combinable Items with Values for a Set-of-items Recommendation2021

    • Author(s)
      Hieu Hanh Le, Yutaka Horino, Tomoyoshi Yamazaki, Kenji Araki, Haruo Yokota
    • Organizer
      The 34 IEEE International Symposium on Computer-based Medical Systems (CBMS 2021)
    • Int'l Joint Research

URL: 

Published: 2022-12-28  

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