학술논문
Evaluation of different decision tree-based methods applied to assessment of bronchial blocking success in patients with destructive forms of tuberculosis
Document Type
Conference
Author
Source
2022 6th Scientific School Dynamics of Complex Networks and their Applications (DCNA) Scientific School Dynamics of Complex Networks and their Applications (DCNA), 2022 6th. :176-178 Sep, 2022
Subject
Language
ISSN
2770-744X
Abstract
We have studied the importance of various lung characteristics obtained by computed tomography (CT), in combination with other factors, for the outcome of endobronchial valve (BV) therapy in patients with destructive lung pathology due to tuberculosis. We have developed predictive models based on the decision tree method and the modern efficient CatBoost algorithm trained on clinical data. This allowed us to identify key characteristics and interactions between them, as well as evaluate the success of endobronchial valve treatment.The constructed models show that the main influence on the positive result of bronchoblocking was provided by non–specific factors (patient’s age and MBT sensitivity) not related to the technique itself.