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Algorithms for anomaly detection in data from clinical trials and health registries
Bondarenko, Maxim ; Blaha, Milan (referee) ; Schwarz, Daniel (advisor)
This master's thesis deals with the problems of anomalies detection in data from clinical trials and medical registries. The purpose of this work is to perform literary research about quality of data in clinical trials and to design a personal algorithm for detection of anomalous records based on machine learning methods in real clinical data from current or completed clinical trials or medical registries. In the practical part is described the implemented algorithm of detection, consists of several parts: import of data from information system, preprocessing and transformation of imported data records with variables of different data types into numerical vectors, using well known statistical methods for detection outliers and evaluation of the quality and accuracy of the algorithm. The result of creating the algorithm is vector of parameters containing anomalies, which has to make the work of data manager easier. This algorithm is designed for extension the palette of information system functions (CLADE-IS) on automatic monitoring the quality of data by detecting anomalous records.
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Algorithms for anomaly detection in data from clinical trials and health registries
Bondarenko, Maxim ; Blaha, Milan (referee) ; Schwarz, Daniel (advisor)
This master's thesis deals with the problems of anomalies detection in data from clinical trials and medical registries. The purpose of this work is to perform literary research about quality of data in clinical trials and to design a personal algorithm for detection of anomalous records based on machine learning methods in real clinical data from current or completed clinical trials or medical registries. In the practical part is described the implemented algorithm of detection, consists of several parts: import of data from information system, preprocessing and transformation of imported data records with variables of different data types into numerical vectors, using well known statistical methods for detection outliers and evaluation of the quality and accuracy of the algorithm. The result of creating the algorithm is vector of parameters containing anomalies, which has to make the work of data manager easier. This algorithm is designed for extension the palette of information system functions (CLADE-IS) on automatic monitoring the quality of data by detecting anomalous records.
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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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Identification of Organisms Based on Analysis of Nucleotide Density Vectors
Maděránková, Denisa ; Babula, Petr (referee) ; Schwarz, Daniel (referee) ; Provazník, Ivo (advisor)
Most methods for analysis of genomic data work with symbolic sequences. Numerically represented genomic sequences can be analyzed by signal processing methods. A new method of numerical representation of DNA sequences, nucleotide density vectors, is proposed in this thesis. Usability of this method for purposes of molecular species identification is tested on DNA barcoding sequences. DNA barcoding is modern and popular methodology based on comparison of short mitochondrial DNA sequences. Beside species identification by proposed method based on nucleotide density vectors, higher taxa rank identification (e.g. families) was also tested. Furthermore, dendrograms were constructed from standardly used evolutionary distances and distances between nucleotide density vectors and the dendrograms were compared.
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Software for automatic data extraction in analysis of brain connectivity
Bujnošková, Eva ; Schwarz, Daniel (referee) ; Jan, Jiří (advisor)
The brain; complex system people want to know about but still they are at the beginning of understanding it. There has been a lot of neuroimaging systems since developement of modern technologies and magnetic resonance imaging is one of them. In last days it isn't enough to examine only structural character of brain, the scientists are dealing with functional states more and more; the functional magnetic resonance imaging is perfectly good tool for this. There is a big amount of researches concerning individual brain regions but also a lot of them dealing with communication across the brain to clear up the causes of human behavior and functional failures. This thesis introduces the brain connectivity exploration, it uses the parcellation by anatomical atlases and it tries to use the knowledge of graph theory as one of the options to determine relations between brain centres and regions. The thesis introduces the software created for extraction of connectivity matrix resulting in graph processing and visualization.
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A comparison of effective and functional connectivity methods in fMRI
Gajdoš, Martin ; Schwarz, Daniel (referee) ; Jan, Jiří (advisor)
Functional magnetic resonance imaging (fMRI) is recent important method, used in neuroimaging. The aim of this thesis is to develop software tool for comparison of two methods for functional and effective connectivity estimation. In this thesis are described the basics of magnetic resonance imaging, fMRI, basic terms of fMRI experiments and generally are described methods of functional and effective connectivity. Then are more detailed mentioned methods of dynamic causal modeling (DCM), Granger causal modeling (GCM) and independent component analysis (ICA). Practical implementation of DCM in toolbox SMP and ICA in toolbox GIFT is also mentioned. In purpose to describe behavior of DCM and GCM in dependence on several parameters are performed Monte Carlo simulations. Then the concept and realization of software tool for simulating connectivity and comparison of DCM and GCM are described. Finally results of DCM and GCM comparison and results of Monte Carlo simulations are discussed.
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Registration of volume CT brain images by means of global affine 3D transform
Mikuláš, Karol ; Schwarz, Daniel (referee) ; Walek, Petr (advisor)
At present, the medical industry rapidly develops new imaging techniques and improves the imaging methods. Simultaneously also are developed new methods for processing data acquired by these methods. Especially in the past few years has become very used method of registration data, which leads to image transformations of the same scene so that the condition as possible. The work deals with the method of processing data that provides detailed information to individual structures, developments of individual structures over time, allows to simultaneously displayanatomical and physiological information or preprocessing data for further processing.
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Image analysis for correction of electron microscopes
Smital, Petr ; Schwarz, Daniel (referee) ; Kolář, Radim (advisor)
This thesis describes the physical nature of corrections of an electron microscope and mathematical methods of image processing required for their complete automation. The corrections include different types of focusing, astigmatism correction, electron beam centring, and image stabilisation. The mathematical methods described in this thesis include various methods of measuring focus and astigmatism, with and without using the Fourier transform, edge detection, histogram operations, and image registration, i.e. detection of spatial transformations in images. This thesis includes detailed descriptions of the mathematical methods, their evaluation using an “offline” application, descriptions of the algorithms of their implementation into an actual electron microscope and results of their testing on the actual electron microscope, in the form of a video footage grabbed from its control computer’s screen.
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