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カワイ ユキコ
KAWAI YUKIKO
河合 由起子 所属 京都産業大学 情報理工学部 情報理工学科 職種 教授 |
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| 発行・発表の年月 | 2023/07 |
| 形態種別 | 研究論文 |
| 査読 | 査読あり |
| 標題 | An early warning model of type 2 diabetes risk based on POI visit history and food access management |
| 執筆形態 | その他 |
| 掲載誌名 | PLOS ONE |
| 出版社・発行元 | Public Library of Science (PLoS) |
| 巻・号・頁 | 18(7),e0288231-e0288231頁 |
| 著者・共著者 | Huaze Xie,Da Li,Yuanyuan Wang,Yukiko Kawai |
| 概要 | Type 2 diabetes (T2D) is a long-term, highly prevalent disease that provides extensive data support in spatial-temporal user case data mining studies. In this paper, we present a novel T2D food access early risk warning model that aims to emphasize health management awareness among susceptible populations. This model incorporates the representation of T2D-related food categories with graph convolutional networks (GCN), enabling the diet risk visualization from the geotagged Twitter visit records on a map. A long short-term memory (LSTM) module is used to enhance the performance of the case temporal feature extraction and location approximate predictive approach. Through an analysis of the resulting data set, we highlight the food effect category has on T2D early risk visualization and user food access management on the map. Moreover, our proposed method can provide suggestions to T2D susceptible patients on diet management. |
| DOI | 10.1371/journal.pone.0288231 |
| ISSN | /1932-6203 |
| PermalinkURL | https://dx.plos.org/10.1371/journal.pone.0288231 |