A Review of Privacy Preserving Mechanisms for Record Linkage

Bonomi, Luca; Fan, Liyue; Xiong, Li

doi:10.1007/978-3-319-23633-9_10

Cited by 3 publications

(2 citation statements)

References 43 publications

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“…All descriptive N values were randomly rounded to base five to maximize patient confidentiality and reduce the risk of residual disclosure. Random rounding is common practice among large-scale, epidemiological studies that examine patient or survey subgroups, and in this study values were randomly rounded within five digits of the actual value (Bonomi, Fan, & Xiong, 2015; Boyd, Randall, & Ferrante, 2015).…”

Section: Methodsmentioning

confidence: 99%

Seasonal variations in psychiatric admissions to hospital.

Slaunwhite¹,

Ronis²,

Peters³

et al. 2019

Canadian Psychology / Psychologie canadienne

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The objective of this study was to identify seasonal variations in mental health–related hospitalizations among children, adolescents, and adults using administrative health data. Hospital admission records from January 2004 to March, 2014 were sourced from the New Brunswick Discharge Abstract Database. Seasonality was measured using a cosinor model to estimate the phase, amplitude, and peak of seasonal variations in psychiatric admissions over the 12-month period from January through December. A general linear model using a Poisson distribution was used to calculate rate ratios that measured the significance of monthly variations in psychiatric admissions. We adjusted for the average number of days per month and provincial population counts using offsets in both models. Between 2004 and 2014, there were 57,730 mental health–related hospital admissions by 41,690 patients. Psychiatric admissions by children and adolescents (aged 3–19 years) increased from 44 admissions per 100,000 in 2004 to 51 admissions per 100,000 in 2014. Rates of psychiatric admissions among children, adolescents, and adults exhibited seasonality confirmed through the detection of a statistically significant sinusoidal pattern (p < .025). The highest rates of child and adolescent admissions were in February (phase = 2, amplitude = 4.4), whereas adult admissions to the hospital peaked in early May (phase = 5.3, amplitude = 9.7). These findings lend support to existing efforts to identify the complex array of individual, family, community, and environmental factors that influence the likelihood of acute care utilization for management of psychiatric disorders.

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Section: Methodsmentioning

confidence: 99%

Seasonal variations in psychiatric admissions to hospital.

Slaunwhite¹,

Ronis²,

Peters³

et al. 2019

Canadian Psychology / Psychologie canadienne

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“…Besides its role in mathematics and physics, the LIS found applications in computer science, where it is suggested as a measure of sortedness of large amounts of data [21] or to find structures in time series while preserving privacy of the data, which is useful in the context of, e.g., fraud detection using financial data streams [22]. Also in bioinformatics the LIS found applications in the context of sequence alignment, e.g., for DNA or protein sequences [23].…”

Section: Introductionmentioning

confidence: 99%

How many longest increasing subsequences are there?

Krabbe,

Schawe,

Hartmann

2020

Preprint

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We study the entropy S of longest increasing subsequences (LIS), i.e., the logarithm of the number of distinct LIS. We consider two ensembles of sequences, namely random permutations of integers and sequences drawn i.i.d. from a limited number of distinct integers. Using sophisticated algorithms, we are able to exactly count the number of LIS for each given sequence. Furthermore, we are not only measuring averages and variances for the considered ensembles of sequences, but we sample very large parts of the probability distribution p(S) with very high precision. Especially, we are able to observe the tails of extremely rare events which occur with probabilities smaller than 10 −600 . We show that the distribution of the entropy of the LIS is approximately Gaussian with deviations in the far tails, which might vanish in the limit of long sequences. Further we propose a large-deviation rate function which fits best to our observed data.

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