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This paper describes the intelligent information system of heterogeneous medical data analysis for Ear Nose Throat (ENT) domain. Machine learning (ML) methods for medical data processing are analyzed. The scenario of machine learning algorithms for data processing in intelligent information system was developed. Supervised learning algorithms for classification task were implemented, their efficiency...
Active anterior rhinomanometry is important method for diagnosis of rhinological disorders. This paper presents the new approach for feature extraction based on chaos theory for tasks of rhinology. It has been demonstrated that rhinomanometric signals have a fractal properties. The usage of phase space diagram for feature extraction for rhinomanometric data was proposed.
The paper presents a new approach for processing of rhinomanometric signals based on F-transform approximation of phase diagrams. Methods of nonlinear dynamics for processing of time series allow us to obtain a significant features of rhinomanometric signals. Research indicated that the results of classification with F-transform approximation is more accurate than results of classification with FFT...
Aerodynamic characteristics of nasal airflow are important for obstruction problems detection. In clinical practice, we analyze behavior of hydrodynamic resistance coefficient. This paper proposes a component of real-time automated system for rhinomanometric measurements. The component is a real-time alert to help users define a correct measurement.
The Active Anterior Rhinomanometry method for an objective assessment of nasal breath is carried out. The preprocessing's methods for rhinomanometric data were analyzed. It was proposed to use the method of fuzzy approximation based on F-transform for preprocessing of rhinomanometric signals.
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