G.G. Abdullayeva, N.O. Alishzade
Modeling the knowledge from healthcare systems for machine learning applications

The paper aims to prove that healthcare data analysis techniques are no longer sufficiently efficient and suitable for managing heterogeneous knowledge issues and improving healthcare data analytics due to the rapid growth and evolution of machine learning techniques.  The application of artificial intelligence facilities helps surpass the human level performance and undeniably improves the diagnosis process. Due to the tremendous advancement of data acquisition in novel diagnostic devices, healthcare data is quite large and even approaching big data, which makes the application of machine learning techniques in the analysis of this data efficient. We work on the data modelling methods for the knowledge from the healthcare sector to improve applicable machine learning methods on it.

Keywords: Heterogeneous knowledge, Knowledge graph, Healthcare data, Machine learning
Institute of Control Systems of the Ministry of Science and Education of the Republic of Azerbaijan
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