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Deep Learning Frailty Model for Heart Failure Survival Prediction
نویسندگان :
Solmaz Norouzi
1
Mohammad Asghari Jafarabadi
2
Ebrahim Hajizadeh
3
Hossein Khormaei
4
Nasim Naderi
5
1- دانشگاه تربیت مدرس
2- Monash university
3- دانشگاه تربیت مدرس
4- دانشگاه ملی مهارت
5- دانشگاه علوم پزشکی ایران
کلمات کلیدی :
Deep Learning،survival analysis،prediction،heart failure
چکیده :
Abstract—The study employed Deep Learning Frailty(DLF), a compelling neural modeling framework for predicting heart failure patient survival. The DLF embeds a notion of multiplicative frailty from classical survival analysis that deals with unobserved heterogeneity while exploiting the neural structure's strong capabilities in approximating any non-linear covariate relationship. Keywords—Deep Learning, prediction, survival analysis, heart failure
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بیشتر
ثمین همایش، سامانه مدیریت کنفرانس ها و جشنواره ها - نگارش 44.5.0
