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Use of quasi-experimental studies to evaluate causal effects of public health interventions in Portugal: a scoping review. [PDF]

BMC Med Res Methodol
Leite A, Kislaya I, Machado A, Aguiar P, Nunes B, Dias CM.   +5 more
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Statistical Data Mining for Time-series Datasets

Statistical Data Mining for Time-series Datasets
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Mining Time Series Data

2015
Temporal data is common in data mining applications. Typically, this is a result of continuously occurring processes in which the data is collected by hardware or software monitoring devices. The diversity of domains is quite significant and extends from the medical to the financial domain.
Yasser Mohammad, Toyoaki Nishida
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Data mining in medical time series

Biomedizinische Technik/Biomedical Engineering, 2006
This article proposes a modular, computer-based methodology to describe and compare medical problems using data mining methods. The methodology focuses on a mathematical formulation of typical classification problems, systematic extraction of interpretable features from time series, and an evaluation adapted to problem-specific preferences and ...
Mikut, R., Reischl, M., Burmeister, O., Loose, T.   +3 more
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Fuzzy data mining for time-series data

Applied Soft Computing, 2012
Time series analysis has always been an important and interesting research field due to its frequent appearance in different applications. In the past, many approaches based on regression, neural networks and other mathematical models were proposed to analyze the time series.
Chun-Hao Chen, Tzung-Pei Hong, Vincent S. Tseng   +2 more
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Mining Time Series Data

2006
Much of the world’s supply of data is in the form of time series. In the last decade, there has been an explosion of interest in mining time series data. A number of new algorithms have been introduced to classify, cluster, segment, index, discover rules, and detect anomalies/novelties in time series. While these many different techniques used to solve
Chotirat Ann Ralanamahatana, Jessica Lin, Dimitrios Gunopulos, Eamonn Keogh, Michail Vlachos, Gautam Das   +5 more
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Mining from Time Series Human Movement Data

2006 IEEE International Conference on Systems, Man and Cybernetics, 2006
Human motion not only contains a wealth of information about actions and intentions, but also about identity and personal attributes of the moving person. Research also indicates that there are positive relationships between the health of a person and their pattern of motion.
Chiu-Che Tseng, Diane Cook
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Flood prediction using Time Series Data Mining

Journal of Hydrology, 2007
Summary This paper describes a novel approach to river flood prediction using Time Series Data Mining which combines chaos theory and data mining to characterize and predict events in complex, nonperiodic and chaotic time series. Geophysical phenomena, including earthquakes, floods and rainfall, represent a class of nonlinear systems termed chaotic ...
Chaitanya Damle, Ali Yalcin
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Preserving Privacy in Time Series Data Mining

International Journal of Data Warehousing and Mining, 2011
Time series data mining poses new challenges to privacy. Through extensive experiments, the authors find that existing privacy-preserving techniques such as aggregation and adding random noise are insufficient due to privacy attacks such as data flow separation attack.
Ye Zhu, Yongjian Fu, Huirong Fu
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Mining Time Series Data: A Selective Survey

2009
Time series prediction and control may involve the study of massive data archive and require some kind of data mining techniques. In order to make the comparison of time series meaningful, one important question is to decide what similarity means and what features have to be extracted from a time series. This question leads to the fundamental dichotomy:
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