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• W4240591098 abstract "Abstract Background: For effective allocations of limited human resources, it is significant to have accurate estimates of future elderly care demands at the regional level, especially in areas where aging and population decline vary by region, such as Hokkaido prefecture in Japan. Objectives: The present study aimed to estimate the numbers of short-stay service recipients in all administrative units in Hokkaido from 2020 to 2045 with the machine learning approaches and reviewed the changing trends of spatial distributions of the service recipients with cartograms. Methods: A machine learning approach was used for the estimation. To develop the model to estimate, population data in Japan from 2015 to 2017 were used as input signals, whereas data on the numbers of short-stay service recipients at each level of needs for long-term care (levels 1–5) from 2015 to 2017 were used as a supervisory signal. Three models were developed to avoid problems of repeatability. Then, data of the projected population in Hokkaido every 5 years from 2020 to 2045 were fed into each model to estimate the numbers of the service recipients for the 188 administrative units of Hokkaido. The medians of the estimations from the models were considered as the final results; the estimates for 188 administrative units were presented with continuous area cartograms on the map of Hokkaido. Results: The developed models predicted that the number of the service recipients in Hokkaido would peak at 18,016 in 2035 and the number of people at level 3 in particular would increase. The cartograms for levels 2 and 3 from 2020 to 2030 and level 3 for 2035 were heavily distorted in the populated areas in Hokkaido. Discussion: The large correlation coefficients indicated the accuracy of estimations by the developed models. The growing number of the service recipients especially at level 3 by 2035 was assumed to be related to aging of the first baby boomers in Japan. The distortions of the cartograms suggested that the majority of the service recipients would be concentrated in the populated areas in Hokkaido. Future allocations of human resources were discussed on the basis of the findings." @default.
• W4240591098 created "2022-05-12" @default.
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• W4240591098 date "2020-11-09" @default.
• W4240591098 modified "2023-09-24" @default.
• W4240591098 title "Estimated Number of Short-Stay Service Recipients in Hokkaido Prefecture, Japan, from 2020 to 2045: Estimation by Machine Learning and Review of Changing Trend by Cartogram" @default.
• W4240591098 doi "https://doi.org/10.21203/rs.3.rs-102898/v1" @default.
• W4240591098 hasPublicationYear "2020" @default.
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