Collection and Construction of database for physiological and physical support of children
Project/Area Number |
24390463
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Research Category |
Grant-in-Aid for Scientific Research (B)
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Allocation Type | Partial Multi-year Fund |
Section | 一般 |
Research Field |
Orthodontic/Pediatric dentistry
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Research Institution | Nagasaki University |
Principal Investigator |
FUJIWARA Taku 長崎大学, 医歯薬学総合研究科 (歯学系), 教授 (00228975)
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Co-Investigator(Kenkyū-buntansha) |
HOSHINO Tomonori 長崎大学, 医歯薬学総合研究科(歯学系), 准教授 (00359960)
NISHIGUCHI Miyuki 長崎大学, 医歯薬学総合研究科(歯学系), 助教 (10253676)
HIDAKA Kiyoshi 長崎大学, 医歯薬学総合研究科(歯学系), 助教 (10389421)
ASADA Yoshinobu 鶴見大学歯学部, 歯学部, 教授 (20184145)
YAMASAKI Youichi 鹿児島大学, 医歯学総合研究科, 教授 (30200645)
KAMASAKI Youko 長崎大学, 医歯薬学総合研究科(歯学系), 助教 (30253678)
MOTOMURA Youichi 独立行政法人産業技術総合研究所, サービス工学研究センター, 副センター長 (30358171)
SAITOH Kan 東北大学, 大学病院, 講師 (40380852)
KARIBE Hiroyuki 日本歯科大学, 歯学部, 教授 (50234000)
YAWAKA Yasutaka 北海道大学, 歯学研究科, 教授 (60230603)
HAYASAKI Haruaki 新潟大学, 医歯学系, 教授 (60238095)
SATOH Kyouko 長崎大学, 病院(歯学系), 助教 (70404499)
SHINTANI Seikou 東京歯科大学, 歯学部, 教授 (90273698)
HIRATA Souichirou 東京歯科大学, 歯学部, 教授 (90433929)
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Project Period (FY) |
2012-04-01 – 2016-03-31
|
Project Status |
Completed (Fiscal Year 2015)
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Budget Amount *help |
¥18,200,000 (Direct Cost: ¥14,000,000、Indirect Cost: ¥4,200,000)
Fiscal Year 2015: ¥1,300,000 (Direct Cost: ¥1,000,000、Indirect Cost: ¥300,000)
Fiscal Year 2014: ¥3,770,000 (Direct Cost: ¥2,900,000、Indirect Cost: ¥870,000)
Fiscal Year 2013: ¥5,330,000 (Direct Cost: ¥4,100,000、Indirect Cost: ¥1,230,000)
Fiscal Year 2012: ¥7,800,000 (Direct Cost: ¥6,000,000、Indirect Cost: ¥1,800,000)
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Keywords | 子ども / タブレット端末 / データベース / 母親教室 / 決定木 / う蝕罹患 / 小児 / ベイズ分析 / 外傷 |
Outline of Final Research Achievements |
The purpose of this study is to analyze the data of patients’ background using machine learning method and to develop an application that could output helpful information. We also tried to construct a new system that will enable to continuously collect and utilize these data using tablet. We included data collection system of dental trauma. Data collection system was completed. We will continue data collection using this system. We tried to make decision tree from questionnaire of the mother class using application Weka (Machine Learning Group at the University of Waikato, New Zealand) . Several decision trees were generated, but we could not obtain proper decision trees according with the conventional theory. Since the contents of the sheet were slightly different at each clinic, missing values were likely to influence the analysis. A unified questionnaires style would be necessary. In addition, selection of the objective variable should be more important.
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Report
(5 results)
Research Products
(4 results)
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[Presentation] Construction of new risk predictive model based on machine learning method2016
Author(s)
Yoshio Kondo, Yoichi Motomura, Keisuke Murayama, Haruka Nishimata, Kayo Nishida, Keigo Imamura, Kyoko Satoh, Kiyoshi Hidaka, Yoko Kamasaki, Miyuki Nishiguchi, Tomonori Hoshino, Kan Saito1, Taku Fujiwara
Organizer
10th Biannial Conference of the Pediatric Dentistry Association of Asia
Place of Presentation
Tokyo Dome Hotel (東京都)
Year and Date
2016-05-26
Related Report
Int'l Joint Research
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