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Zhaohui Zou

Researcher at Silver Spring Networks

Publications -  16
Citations -  11771

Zhaohui Zou is an academic researcher from Silver Spring Networks. The author has contributed to research in topics: Population & Cancer. The author has an hindex of 10, co-authored 16 publications receiving 11172 citations.

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Journal ArticleDOI

Cancer statistics, 2014

TL;DR: The magnitude of the decline in cancer death rates from 1991 to 2010 varies substantially by age, race, and sex, ranging from no decline among white women aged 80 years and older to a 55% decline among black men aged 40 years to 49 years.
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Efficient interval estimation for age-adjusted cancer rates.

TL;DR: The proposed gamma and F intervals and the normal intervals for the correlated age-adjusted rates are recommended to be implemented in the Surveillance, Epidemiology and End Results Program of the National Cancer Institute.
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Estimating average annual percent change for disease rates without assuming constant change.

TL;DR: This work calls this parameter the percent change annualized (PCA) and proposes two new estimators of it, an adaptive one and equals the linear model estimator with a high probability when the rates are not significantly different from linear on the log scale, but includes fewer points if there are significant departures from that linearity.
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A new method of estimating United States and state-level cancer incidence counts for the current calendar year.

TL;DR: A new method is presented that uses statistical models of cancer incidence that incorporate potential predictors of spatial and temporal variation of cancer occurrence and that account for delay in case reporting and then projects these estimated numbers of cases ahead 4 years using a piecewise linear (joinpoint) regression method.
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Weighted Normal Spatial Scan Statistic for Heterogeneous Population Data

TL;DR: A weighted normal scan statistic is proposed for investigating the clusters of the cells (geographic units such as counties) with unusual high/low continuous regional measures, where the weights reflect the uncertainty of the regional measures or sample size in the cells.