Evolving forecasting classifications and applications in health forecasting.
about
An overview of health forecastingSemistructured black-box prediction: proposed approach for asthma admissions in LondonJoint Analyses of Longitudinal and Time-to-Event Data in Research on Aging: Implications for Predicting Health and Survival.Humans as animal sentinels for forecasting asthma events: helping health services become more responsive.Forecasting peak asthma admissions in London: an application of quantile regression models.Informing management on the future structure of hospital care: an extrapolation of trends in demand and costs in lung diseases.Forecasting asthma-related hospital admissions in London using negative binomial models.Disease management with ARIMA model in time series.Assessment of autoregressive integrated moving average (ARIMA), generalized linear autoregressive moving average (GLARMA), and random forest (RF) time series regression models for predicting influenza A virus frequency in swine in Ontario, Canada.
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Evolving forecasting classifications and applications in health forecasting.
description
2012 nî lūn-bûn
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2012年の論文
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2012年学术文章
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2012年学术文章
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2012年学术文章
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2012年学术文章
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2012年學術文章
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name
Evolving forecasting classifications and applications in health forecasting.
@en
type
label
Evolving forecasting classifications and applications in health forecasting.
@en
prefLabel
Evolving forecasting classifications and applications in health forecasting.
@en
P2860
P356
P1476
Evolving forecasting classifications and applications in health forecasting.
@en
P2860
P304
P356
10.2147/IJGM.S31079
P407
P577
2012-05-08T00:00:00Z