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National Repository of Grey Literature 2 records found  Search took 0.00 seconds. 
Predicting novel drug-target interactions via deep learning techniques
 Frey, Adam ; Peška, Ladislav (advisor) ; Kratochvíl, Miroslav (referee)
Adam Frey Aim of this work was to develop a machine-learning model for a prediction of drug-target interactions. Inspired by previous state-of-the-art approaches, the work focuses on collaborative filtering methods and deep learning neural network models. The goal of improving upon the previous work was achieved using a series of improvements of a basic latent matrix factorization algorithm on the relevant dataset. The small amount of data currently seems like the bottleneck for utilizing more sophisticated deep learning methods. As such hybrid approaches for recommendation systems can prove to be interesting next step due to their effective utilization of multiple data sources.
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Detection of malignant melanoma in histological sample using deep neural networks
 Frey, Adam ; Lokoč, Jakub (advisor) ; Straka, Milan (referee)
The aim of this thesis is to create a classification method for detection of ma- lignant melanoma in high-resolution digital images. Deep convolutional neural networks were used for this task. At first, a short overview of malignant melanoma and ways to detect it is presented. Deep convolutional neural networks are also introduced with a special attention given to models used further in this work. Several ways to generate samples from the provided histological images are discussed, and several experiments are evaluated to decide how to maximize the accuracy of employed classification methods. The thesis then focuses on several neural network structures used for image classification and their possible utiliza- tion for the given task. The emphasis is laid on the transfer learning, a method used for modifying already trained models for different tasks. This method is then used for training several classifiers. Further on, several methods for the visualization of model results are discussed with some of them implemented. The experiments show promising results on par with other studies dealing with similar problems. Several possibilities for further development are listed in the conclusion.
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