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Paper Abstract and Keywords
Presentation 2023-03-13 15:30
Proposal of emergency demand forecasting method based on population projection data by age using large-scale emergency data
Masaki Kaneda, Sinan Chen, Masahide Nakamura (Kobe Univ), Sachio Saiki (Kochi Univ of Technology of) LOIS2022-54
Abstract (in Japanese) (See Japanese page) 
(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) 
(in English) emergency demand / Aging society / medical stringency / / / / /  
Reference Info. IEICE Tech. Rep., vol. 122, no. 423, LOIS2022-54, pp. 59-65, March 2023.
Paper # LOIS2022-54 
Date of Issue 2023-03-06 (LOIS) 
ISSN Online edition: ISSN 2432-6380
Copyright
and
reproduction		 All rights are reserved and no part of this publication may be reproduced or transmitted in any form or by any means, electronic or mechanical, including photocopy, recording, or any information storage and retrieval system, without permission in writing from the publisher. Notwithstanding, instructors are permitted to photocopy isolated articles for noncommercial classroom use without fee. (License No.: 10GA0019/12GB0052/13GB0056/17GB0034/18GB0034)
Download PDF LOIS2022-54

Conference Information
Committee LOIS  
Conference Date 2023-03-13 - 2023-03-14 
Place (in Japanese) (See Japanese page) 
Place (in English)  
Topics (in Japanese) (See Japanese page) 
Topics (in English)  
Paper Information
Registration To LOIS 
Conference Code 2023-03-LOIS 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Proposal of emergency demand forecasting method based on population projection data by age using large-scale emergency data 
Sub Title (in English)  
Keyword(1) emergency demand  
Keyword(2) Aging society  
Keyword(3) medical stringency  
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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)
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Speaker Author-1 
Date Time 2023-03-13 15:30:00 
Presentation Time 25 minutes 
Registration for LOIS 
Paper # LOIS2022-54 
Volume (vol) vol.122 
Number (no) no.423 
Page pp.59-65 
#Pages 7 
Date of Issue 2023-03-06 (LOIS) 

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