A Simple Optimal Randomized Algorithm for Sorting on the PDM

Rajasekaran, Sanguthevar; Sen, Sandeep

doi:10.1007/11602613_55

Cited by 4 publications

(1 citation statement)

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“…TSLink2 is capable of linking very large number of records. Even if the size of data is too big to fit into main memory, out-of-core sorting algorithms, for example [24][25][26][27][28] , could be employed to sort the two sequences described above in an out-of-core fashion.…”

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confidence: 99%

A fast privacy-preserving patient record linkage of time series data

Soliman

Rajasekaran

Toman

et al. 2023

Sci Rep

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Recent advances in technology have led to an explosion of data in virtually all domains of our lives. Modern biomedical devices can acquire a large number of physical readings from patients. Often, these readings are stored in the form of time series data. Such time series data can form the basis for important research to advance healthcare and well being. Due to several considerations including data size, patient privacy, etc., the original, full data may not be available to secondary parties or researchers. Instead, suppose that a subset of the data is made available. A fast and reliable record linkage algorithm enables us to accurately match patient records in the original and subset databases while maintaining privacy. The problem of record linkage when the attributes include time series has not been studied much in the literature. We introduce two main contributions in this paper. First, we propose a novel, very efficient, and scalable record linkage algorithm that is employed on time series data. This algorithm is 400× faster than the previous work. Second, we introduce a privacy preserving framework that enables health institutions to safely release their raw time series records to researchers with bare minimum amount of identifying information.

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confidence: 99%