Development of Advanced Analytical Technology for Llarge-scale Medical Data

2017 Fiscal Year Final Research Report

• Project/Area Number: 15H02705
• Research Category: Grant-in-Aid for Scientific Research (B)
• Allocation Type: Single-year Grants
• Section: 一般
• Research Field: Multimedia database
• Research Institution: Kumamoto University
• Principal Investigator: Sakurai Yasushi 熊本大学, 大学院先端科学研究部(工), 教授 (30466411)
• Co-Investigator(Kenkyū-buntansha): 有次 正義 熊本大学, 大学院先端科学研究部(工), 教授 (40282412) ; 吉川 正俊 京都大学, 情報学研究科, 教授 (30182736) ; 今中 雄一 京都大学, 医学研究科, 教授 (10256919)
• Research Collaborator: Faloutsos Christos カーネギーメロン大学, Dept. of Computer Science, 教授
• Project Period (FY): 2015-04-01 – 2018-03-31
• Keywords: 医療情報 / 時系列解析 / 予測

Outline of Final Research Achievements

With the aim of improving health care and medical services, we develop a unifying advanced analytical technology that will make it possible to extract latent relationships in complex time-stamped medical data (e.g., electronic medical records). Medical data analytical technology is considered important throughout the world. Our developed method can identify important dynamical patterns and forecast long-range future events, incrementally and automatically.

Free Research Field

データマイニング