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Methods of Biomedical Informatics in the study of inflammatory bowel disease in children
Čopová, Ivana ; Hradský, Ondřej (advisor) ; Ďuricová, Dana (referee) ; Krupička, Radim (referee)
METHODS OF BIOMEDICAL INFORMATICS IN THE STUDY OF INFLAMMATORY BOWEL DISEASE IN CHILDREN Abstract Inflammatory bowel diseases (IBD) are a group of chronic, polygenic diseases primarily affecting the gastrointestinal tract, with an increasing incidence in both adult and paediatric populations globally. These diseases include Crohn's disease (CD), ulcerative colitis (UC) and so-called IBD unclassified (IBD-U). Faecal calprotectin (FC) is a marker of inflammation in IBD and its levels correlate with disease activity as defined by clinical parameters, endoscopic findings and histology. Current medical practice is associated with the availability of a large amount of clinical data and the desire to apply it effectively in the medical decision-making process in such a way as to achieve the maximum possible reduction in the risk of adverse disease course and the occurrence of disease- and/or treatment-associated complications. The primary goal of this dissertation is to apply biomedical informatics methods to paediatric IBD in the process of validating FC in predicting disease activity and response to treatment, searching for additional potential predictive factors, and developing prediction models for specific clinical situations. We found that the development of FC levels in the early phase of induction therapy...
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Prediction of effects of single point mutations on protein-nucleic acids interactions
Štěpánková, Věra Tereza ; Novotný, Marian (advisor) ; Neuwirthová, Tereza (referee)
Single point mutations are the most common type of mutations and many of them can have pathogenic effects, it is therefore useful to be able to correctly and effectively predict their impact on a given protein. Proteins interacting with nucleic acids are essential for most cellular processes. Progress in computational methods and machine learning enables the development of increasingly high-quality tools for predicting the effect of mutations on proteins. An important category of these predictors are tools for predicting the effect of single point mutations on protein interactions with nucleic acids. This thesis focuses on currently available tools for prediction of missense mutation effect on protein-NA interactions, which predict quantitative changes in protein and nucleic acid affinity and estimate the severity of the mutation based on this change. Attention is also paid to methods for evaluating the quality of predictions of individual tools. Keywords: point mutation, prediction, interaction, mechanism
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Assessing Economic Situation of a Company and Proposals for Its Improvement
Rybár, Tomáš ; Novotná, Veronika (referee) ; Doubravský, Karel (advisor)
The diploma thesis focuses on the assessment of the economic situation of Prefa Brno a.s. and possible suggestions for improving its performance. The theoretical part of the thesis is devoted to the explanation of the concepts of financial and statistical analysis. These concepts are then applied in the analytical part. From the financial analysis, the difference and ratio indicators are evaluated, supplemented by a set of indicators. Regression analysis is performed on selected ratios with a forecast for the following period and correlation analysis is used to identify the interrelationships between them. Conclusions are drawn from the results, which are used to formulate possible measures to improve the current economic situation of the entity under study.
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Models for Predicting Business Financial Performance
Vakhrushev, Dmitrii ; Oulehla, Jiří (referee) ; Luňáček, Jiří (advisor)
The thesis focuses on models for predicting the financial performance of the ALZA company, where it focused on emphasizing the strong financial performance and stability of the company. Key factors contributing to ALZA's success will be mentioned, such as consistent revenues, profits, effective cost management and investment in innovation. In addition, the work would also focus on potential strategies for further growth, such as exploring new markets, strengthening online sales, diversifying product offerings, and strengthening relationships with customers and suppliers. Emphasizing the importance of continuous innovation, market monitoring and strategic investment will demonstrate ALZA's readiness for future success and market expansion.Using financial data for the period 2017 to 2022, market trends and industry benchmarks, accurate predictions can be made regarding ALZA's future financial results. Implementing advanced modelling techniques and incorporating different scenarios can provide valuable insights for strategic decision-making.
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Prediction of future air quality
Roháček, Adam ; Sekora, Jiří (referee) ; Čmiel, Vratislav (advisor)
This thesis explores the prediction of future air quality as a critical aspect of environmental health and sustainable development. With the increasing concerns over air pollution and its detrimental effects on human health and the environment, there is a growing need for accurate forecasting techniques to anticipate and mitigate potential air quality issues. This thesis introduces the reader to the topic of air pollution, describes the usage of prediction algorithms and evaluates quality of the own algorithm.
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Predicting the success of football players using machine learning methods
Janeček, Jan ; Filipenská, Marina (referee) ; Ředina, Richard (advisor)
This bachelor thesis focuses on the implementation of an artificial neural network in the Python programming language using the Keras library. The aim of the work is the numerical prediction of a football player’s match readiness on a scale from 0 to 1. The prediction is based on five physiological-kinematic data obtained from three training sessions preceding a given match. The reference data for training the artificial neural network includes technical data on the number of successful and total actions during the match. The data used in this work was collected from Sigma Olomouc U19 football club players using Polar Team Pro and Wyscout software. The lowest recorded model error, which was 0.1046, was achieved using a single hidden layer containing 15 perceptrons.
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Air quality measurement with prediction
Sadriyeva, Kamilya ; Janoušek, Oto (referee) ; Čmiel, Vratislav (advisor)
This work focuses on the issue of measuring and predicting indoor air quality using the Python programming language. It includes an analysis of existing methods for air quality monitoring, the design of a data collection model, the creation of a predictive model, and the application of computational algorithms to address this issue.
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Health assessment using smart devices
Vargová, Enikö ; Filipenská, Marina (referee) ; Němcová, Andrea (advisor)
This thesis deals with the possibilities of non-invasive determination of blood glucose from photoplethysmographic signals. Elevated blood sugar is often associated with disease called diabetes mellitus. Diabetes is one of the world’s major chronic diseases. Untreated diabetes is often a cause of death. The aim of the work is to propose methods for glycemic classification and prediction. Two datasets have been created by recording the PPG signals using two smart devices (a smart wristband and a smartphone), along with their blood glucose levels measured in an invasive way. The PPG signals were preprocessed, and suitable features were extracted from them. Various machine-learning models for glycemic classification and prediction were created.
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Temperature Profile in Reflow Soldering and Influence of Different PCBś and ComponentsThermal Capacities
Procházka, Martin ; Špinka, Jiří (referee) ; Starý, Jiří (advisor)
This thesis mainly deals with the prediction of temperature on the components and the PCB during reflow soldering. The theoretical part describes the particular solder reflow process, types of heat transfer and temperature profiles. The practical part is divided into forecasting temperatures if the conveyor is stopped and the temperature predictions when the conveyor is in motion. In both parts of the measured temperature is compared with the predicted temperatures, which show the success rate of prediction. The last part of this work is part of the simulation, which helps in proper understanding of the issues discussed.
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Risk Management of Bank Credit System and Decision Making Process
Skovajsa, Radek ; Kryštof, Zdeněk (referee) ; Čižinská, Romana (advisor)
The theoretical part of this thesis describes the development of Czech banking sector, especially with emphasis on post-revolutionary rebirth within the new conditions of market economy. The following part demonstrates the decision-making credit account process of a bank on a particular case study based on the methodics and procedures leading up to maximal elimination of credit risk. At the same time, the author presents a partially modified internal opinion on a decision of particular business transaction. It is accented that every decision of a bank must comply with the regulations of CNB. The conclusion of the thesis affirms the maximal efforts of domestic banks to minimalize risks within their decision-making credit account processes, which is mirrored in current stability in the development of Czech banking sector.
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