چکیده مقاله
Predicting the survival of patients with heart failure HF is crucial for improving the management of CVD This study aimed to model a cause specific Cox CSC deep neural network for predicting the survival of patients with heart failure using a competing risk approach Our retrospective study included 435 patients treated for heart failure at Rajaie Cardiovascular Medical and Research Center in Iran from 2018 to 2023 Patient survival data were analyzed based on the cause of death In this study, instead of feature selection, which is targeted by most classical methods, we introduce a combined approach to provide a flexible and general framework for survival analysis and interpretation In this approach, the random survival forest RSF model first selects features, and then the deep survival model is fitted to the significant variables Finally, the hazard ratio HR of the variables was calculated using the multivariable CSC model The performance of the models was evaluated based on the c index of the training and test sets The deepSurv model showed the best performance, with c index values of 0 58 and 0 66 for the training set and the test set, respectively, for the risk of mortality due to HF For the risk of mortality due to other causes, the RSF had a c index of 0 61/0 66 Finally, for both causes of death, the CSC model demonstrated high accuracy, indicating its usefulness in predicting these outcomes These results emphasize the importance of accurately predicting HF patient survival and identifying risk factors to inform treatment decisions and improve patient outcomes and suggest that survival prediction becomes more accurate when RSF and deepSurv models are used together
کلیدواژهها
نویسندگان
Solmaz Norouzi
Department of Biostatistics, Faculty of Medical Sciences, Tarbiat Modares University, Tehran, Iran
Mohammad Asghari Jafarabadi
Cabrini Research, Cabrini Health, VIC ۳۱۴۴, Australia
Ebrahim Hajizadeh
School of Public Health and Preventative Medicine, Faculty of Medicine, Nursing and Health Sciences, Monash University, VIC ۳۰۰۴, Melbourne Australia
شیوه ارجاع
Norouzi, Solmaz and Asghari Jafarabadi, Mohammad and Hajizadeh, Ebrahim,1403,DeepSurvCompeting Risk: Cause-Specific Cox Deep Neural Network for Predicting Heart Failure Patient's Survival,1st International Biennial Conference of Artificial Intelligence and Data Science 2024,Bushehr
ارائهشده در
مجموعه مقالات اولین کنفرانس بین المللی دوسالانه هوش مصنوعی و علوم داده3 اردیبهشت 1403 · بوشهر