National Repository of Grey Literature 3 records found  Search took 0.00 seconds. 
Computer-aided data quality monitoring and assessment in clinical research
Šiška, Branislav ; Kolářová, Jana (referee) ; Schwarz, Daniel (advisor)
The diploma thesis deals with the monitoring and evaluation of data in clinical research. Usual methods to identify incorrect data are one-dimensional statistical methods per each variable in the register. Proposed method enters directly into database and finds out outliers in data using machine learning combined with multidimensional statistical methods that transform all column variables of clinical register to one, representing one record of patient in the register. Algorithm of proposed method is written in Matlab.
Multidimensional Detection Of Outliers In Clinical Registers
Šiška, Branislav
Incorrect data in clinical registers can lead to inaccurate or wrong results. This project is aimed at monitoring and evaluation of data in clinical registers. Usual methods to identify incorrect data are one-dimensional statistical methods per each variable in the register. Proposed method finds outliers in data using machine learning combined with multidimensional statistical methods that transform all column variables of clinical register to one, representing one record of a patient in the register.
Computer-aided data quality monitoring and assessment in clinical research
Šiška, Branislav ; Kolářová, Jana (referee) ; Schwarz, Daniel (advisor)
The diploma thesis deals with the monitoring and evaluation of data in clinical research. Usual methods to identify incorrect data are one-dimensional statistical methods per each variable in the register. Proposed method enters directly into database and finds out outliers in data using machine learning combined with multidimensional statistical methods that transform all column variables of clinical register to one, representing one record of patient in the register. Algorithm of proposed method is written in Matlab.

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