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Information × Registration Number 0224U001475, 0120U100025 , R & D reports Title Methods and means of processing, consolidating and analyzing personalized medical information popup.stage_title Head Melnykova Nataliya I., Кандидат технічних наук Registration Date 23-01-2024 Organization Lviv Polytechnic National University popup.description2 A model of displaying the patient's condition in a multidimensional space of conditions was developed, which, due to additional measurements and parameters, ensured an increase in the accuracy of forecasting; a method of two-stage processing of small data sets based on a hierarchical predictor, which, due to clustering and forecasting, ensures an increase in the accuracy of processing new input data sets; a method of grouping machine learning models, which, taking into account the main features and repeated training, ensures an increase in the accuracy of data prediction; the method of reducing the dimensionality of the input data, which, thanks to classifiers, associative rules and the generalized rank of features based on the Jacquard index, ensures an increase in the accuracy of selecting priority features on large data sets. The method of filling data gaps has been improved, which, using associative and production rules, ensures the improvement of the model's resistance to data errors; the method of finding a change in the patient's condition, which, using the space of conditions and the analysis of the characteristics of the condition, ensures an increase in the accuracy of the selection of the treatment scheme; the method of multimodal data consolidation, which provides aggregation of data with different structures due to the preliminary determination of the structure and semantics of the data. The theory of support for personalized decision-making was further developed, which is based on the development of a model for displaying the patient's condition in a multidimensional space of conditions and the developed methods of two-stage processing of small data sets, grouping of machine learning models, reducing the dimensionality of input data, filling data gaps, searching for changes in the patient's condition and consolidation multimodal data. The developed methods were used to develop software modules of information systems for decision-making support. Product Description popup.authors Basystiuk Oleh Boyko Natalya I Brusencov Heorhii Vyklyuk Yaroslav I. Vovk Olena B Zavaliy Taras Zagorodniy Ivan Paterega Yurii Pobereyko Petro Skopvskiy Stepan Fedushko Solomiia S. Tsap Vladyslav Shakhovska Natalya Bogdanivna popup.nrat_date 2024-01-23 Close