| Presentation | 2023-03-13 Proposal of long-term emergency demand forecasting method based on large-scale emergency data and age-specific population projection data Masaki Kaneda, Sinan Chen, Masahide Nakamura, Sachio Saiki, |
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| PDF Download Page |  PDF download Page Link |
| Abstract(in Japanese) | (See Japanese page) |
| Abstract(in English) | In recent years, Japan is facing a super-aging society, which has a wide range of impacts. In particular, the tightness of emergency medical care and the increase in the number of ambulance transports are quite serious problems, and urgent measures are required. In response to this situation, our research group is conducting joint research with the Kobe City Fire Department. The purpose is to provide an index for the strategic deployment of ambulance crews and scale expansion/decrease at medical sites. This medium- to long-term prediction of the number of transported cases is realized by analyzing emergency big data, population records, and future population projections in each region without using machine learning. In order to evaluate this proposed method, evaluation verification was performed in Kobe city. As a result, it can be said that the prediction of the number of transported cases by this proposed method is a reasonable result even from the past record of the number of transported cases in Kobe City. In addition, in order to provide indicators for strategic deployment in the emergency medical field, which is the goal, it is necessary to be able to predict the trend of specific number of transports and the maximum number of transports with a prediction accuracy of about 95% or more. was found. Based on this result, this method for predicting the number of cases of ambulance transportation has been established, and it is expected to improve the efficiency of emergency medical sites in various parts of Japan and improve the work style. |
| Keyword(in Japanese) | (See Japanese page) |
| Keyword(in English) | emergency demand / Aging society / medical stringency |
| Paper # | LOIS2022-54 |
| Date of Issue | 2023-03-06 (LOIS) |
| Conference Information | |
| Committee | LOIS |
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| Conference Date | 2023/3/13(2days) |
| Place (in Japanese) | (See Japanese page) |
| Place (in English) | |
| Topics (in Japanese) | (See Japanese page) |
| Topics (in English) | |
| Chair | Hiroyuki Toda(NTT) |
| Vice Chair | Manabu Motegi(Takushoku Univ.) |
| Secretary | Manabu Motegi(Nagasaki Univ.) |
| Assistant | Syuhei Yamamoto(NTT) |
| Paper Information | |
| Registration To | Technical Committee on Life Intelligence and Office Information Systems |
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| Language | JPN |
| Title (in Japanese) | (See Japanese page) |
| Sub Title (in Japanese) | (See Japanese page) |
| Title (in English) | Proposal of long-term emergency demand forecasting method based on large-scale emergency data and age-specific population projection data |
| Sub Title (in English) | |
| Keyword(1) | emergency demand |
| Keyword(2) | Aging society |
| Keyword(3) | medical stringency |
| 1st Author's Name | Masaki Kaneda |
| 1st Author's Affiliation | Kobe University(Kobe Univ) |
| 2nd Author's Name | Sinan Chen |
| 2nd Author's Affiliation | Kobe University(Kobe Univ) |
| 3rd Author's Name | Masahide Nakamura |
| 3rd Author's Affiliation | Kobe University(Kobe Univ) |
| 4th Author's Name | Sachio Saiki |
| 4th Author's Affiliation | Kochi University of Technology(Kochi Univ of Technology of) |
| Date | 2023-03-13 |
| Paper # | LOIS2022-54 |
| Volume (vol) | vol.122 |
| Number (no) | LOIS-423 |
| Page | pp.pp.59-65(LOIS), |
| #Pages | 7 |
| Date of Issue | 2023-03-06 (LOIS) |