Development of computer system for stress reduction and secure improvement on ophthalmology treatments
Project/Area Number |
16K00431
|
Research Category |
Grant-in-Aid for Scientific Research (C)
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Allocation Type | Multi-year Fund |
Section | 一般 |
Research Field |
Web informatics, Service informatics
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Research Institution | University of Hyogo |
Principal Investigator |
|
Research Collaborator |
Tabuchi Hitoshi
|
Project Period (FY) |
2016-04-01 – 2019-03-31
|
Project Status |
Completed (Fiscal Year 2018)
|
Budget Amount *help |
¥4,290,000 (Direct Cost: ¥3,300,000、Indirect Cost: ¥990,000)
Fiscal Year 2018: ¥1,170,000 (Direct Cost: ¥900,000、Indirect Cost: ¥270,000)
Fiscal Year 2017: ¥1,170,000 (Direct Cost: ¥900,000、Indirect Cost: ¥270,000)
Fiscal Year 2016: ¥1,950,000 (Direct Cost: ¥1,500,000、Indirect Cost: ¥450,000)
|
Keywords | 待ち時間予測 / 院内滞在時間予測 / 個人認証 / 左右眼識別 / 畳み込みニューラルネットワーク / 眼科医療支援 / ストレス / クオリティ・オブ・ビジョ ン / 検査種自動決定 / ソフトコンピューティング / 入退室管理 / 屈折度計算式 / クオリティ・オブ・ビジョン / 個人認識 / 医療・福祉 / 待ち時間対策 / 検査種決定 / 入退室管理システム |
Outline of Final Research Achievements |
The objective of this study is to develop systems useful in reducing the mental stress of ophthalmologic patients and in achieving secure improvements for ophthalmologic practices. First, a system of predicting binding time for ophthalmologic outpatients was developed. It can reduce the prediction error for waiting time within 30 minutes, and access database associated with public transport to provide transit time for the outpatients using it. Next, a system of identifying ophthalmologic patients was developed. It prepares identification data from OCT inspection results. Next, a method of achieving high accuracy in discriminating right and left eyes was developed for ophthalmic surgery. It is based on convolutional neural networks. In addition, a system of determining examinations was proposed for ophthalmologic outpatients, using neural networks. It prepares data for network training and examination determination from handwriting sentences in interview sheets.
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Academic Significance and Societal Importance of the Research Achievements |
本研究で開発した所要時間提示システムは直接的待ち時間対策の一環であり,問診票個人情報からの検査種決定システムも,医師の問診票チェックを省くとともに待ち時間の有効利用をモチベーションとしている.待ち時間は患者が通院を躊躇する一因であり,「気がつけば最悪の事態」に陥ることを防ぐことから,本研究は医療コスト削減に貢献できる.また,高齢化により白内障罹患者数も激増し,重大医療事故発生の危険性が増している.OCT検査データのみ用いる本研究の認証システム,手術動画を用いた左右眼識別システムは患者および患部取り違えに起因する医師,患者双方のストレスを大きく削減するとともに,安全性も大きく向上させる.
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Report
(4 results)
Research Products
(11 results)