Prediction of Important Factors for Bleeding in Liver Cirrhosis Disease Using Ensemble Data Mining Approach
Само за регистроване кориснике
2020
Аутори
Aleksić, AleksandarNedeljković, Slobodan
Jovanović, Mihailo
Ranđelović, Miloš
Vuković, Marko
Stojanović, Vladica
Radovanović, Radovan
Ranđelović, Milan
Ranđelović, Dragan
Чланак у часопису (Објављена верзија)
Метаподаци
Приказ свих података о документуАпстракт
The main motivation to conduct the study presented in this paper was the fact that due to the development of improved solutions for prediction risk of bleeding and thus a faster and more accurate diagnosis of complications in cirrhotic patients, mortality of cirrhosis patients caused by bleeding of varices fell at the turn in the 21th century. Due to this fact, an additional research in this field is needed. The objective of this paper is to develop one prediction model that determines most important factors for bleeding in liver cirrhosis, which is useful for diagnosis and future treatment of patients. To achieve this goal, authors proposed one ensemble data mining methodology, as the most modern in the field of prediction, for integrating on one new way the two most commonly used techniques in prediction, classification with precede attribute number reduction and multiple logistic regression for calibration. Method was evaluated in the study, which analyzed the occurrence of variceal... bleeding for 96 patients from the Clinical Center of Nis, Serbia, using 29 data from clinical to the color Doppler. Obtained results showed that proposed method with such big number and different types of data demonstrates better characteristics than individual technique integrated into it.
Кључне речи:
ensemble techniques / data mining / classification and discrimination / linear regression / applied mathematics general / prediction theory / theory of mathematical modeling / medical applicationsИзвор:
Mathematics, 2020, 8, 11, 1887-Издавач:
- Basel : MDPI
Институција/група
JakovTY - JOUR AU - Aleksić, Aleksandar AU - Nedeljković, Slobodan AU - Jovanović, Mihailo AU - Ranđelović, Miloš AU - Vuković, Marko AU - Stojanović, Vladica AU - Radovanović, Radovan AU - Ranđelović, Milan AU - Ranđelović, Dragan PY - 2020 UR - https://jakov.kpu.edu.rs/handle/123456789/1637 AB - The main motivation to conduct the study presented in this paper was the fact that due to the development of improved solutions for prediction risk of bleeding and thus a faster and more accurate diagnosis of complications in cirrhotic patients, mortality of cirrhosis patients caused by bleeding of varices fell at the turn in the 21th century. Due to this fact, an additional research in this field is needed. The objective of this paper is to develop one prediction model that determines most important factors for bleeding in liver cirrhosis, which is useful for diagnosis and future treatment of patients. To achieve this goal, authors proposed one ensemble data mining methodology, as the most modern in the field of prediction, for integrating on one new way the two most commonly used techniques in prediction, classification with precede attribute number reduction and multiple logistic regression for calibration. Method was evaluated in the study, which analyzed the occurrence of variceal bleeding for 96 patients from the Clinical Center of Nis, Serbia, using 29 data from clinical to the color Doppler. Obtained results showed that proposed method with such big number and different types of data demonstrates better characteristics than individual technique integrated into it. PB - Basel : MDPI T2 - Mathematics T1 - Prediction of Important Factors for Bleeding in Liver Cirrhosis Disease Using Ensemble Data Mining Approach VL - 8 IS - 11 SP - 1887 DO - 10.3390/math8111887 ER -
@article{ author = "Aleksić, Aleksandar and Nedeljković, Slobodan and Jovanović, Mihailo and Ranđelović, Miloš and Vuković, Marko and Stojanović, Vladica and Radovanović, Radovan and Ranđelović, Milan and Ranđelović, Dragan", year = "2020", abstract = "The main motivation to conduct the study presented in this paper was the fact that due to the development of improved solutions for prediction risk of bleeding and thus a faster and more accurate diagnosis of complications in cirrhotic patients, mortality of cirrhosis patients caused by bleeding of varices fell at the turn in the 21th century. Due to this fact, an additional research in this field is needed. The objective of this paper is to develop one prediction model that determines most important factors for bleeding in liver cirrhosis, which is useful for diagnosis and future treatment of patients. To achieve this goal, authors proposed one ensemble data mining methodology, as the most modern in the field of prediction, for integrating on one new way the two most commonly used techniques in prediction, classification with precede attribute number reduction and multiple logistic regression for calibration. Method was evaluated in the study, which analyzed the occurrence of variceal bleeding for 96 patients from the Clinical Center of Nis, Serbia, using 29 data from clinical to the color Doppler. Obtained results showed that proposed method with such big number and different types of data demonstrates better characteristics than individual technique integrated into it.", publisher = "Basel : MDPI", journal = "Mathematics", title = "Prediction of Important Factors for Bleeding in Liver Cirrhosis Disease Using Ensemble Data Mining Approach", volume = "8", number = "11", pages = "1887", doi = "10.3390/math8111887" }
Aleksić, A., Nedeljković, S., Jovanović, M., Ranđelović, M., Vuković, M., Stojanović, V., Radovanović, R., Ranđelović, M.,& Ranđelović, D.. (2020). Prediction of Important Factors for Bleeding in Liver Cirrhosis Disease Using Ensemble Data Mining Approach. in Mathematics Basel : MDPI., 8(11), 1887. https://doi.org/10.3390/math8111887
Aleksić A, Nedeljković S, Jovanović M, Ranđelović M, Vuković M, Stojanović V, Radovanović R, Ranđelović M, Ranđelović D. Prediction of Important Factors for Bleeding in Liver Cirrhosis Disease Using Ensemble Data Mining Approach. in Mathematics. 2020;8(11):1887. doi:10.3390/math8111887 .
Aleksić, Aleksandar, Nedeljković, Slobodan, Jovanović, Mihailo, Ranđelović, Miloš, Vuković, Marko, Stojanović, Vladica, Radovanović, Radovan, Ranđelović, Milan, Ranđelović, Dragan, "Prediction of Important Factors for Bleeding in Liver Cirrhosis Disease Using Ensemble Data Mining Approach" in Mathematics, 8, no. 11 (2020):1887, https://doi.org/10.3390/math8111887 . .