Reverse Survival Model (RSM): A Pipeline for Explaining Predictions of Deep Survival Models

no code implementations • 27 Oct 2022 • Mohammad R. Rezaei, Reza Saadati Fard, Ebrahim Pourjafari, Navid Ziaei, Amir Sameizadeh, Mohammad Shafiee, Mohammad Alavinia, Mansour Abolghasemian, Nick Sajadi

The aim of survival analysis in healthcare is to estimate the probability of occurrence of an event, such as a patient's death in an intensive care unit (ICU).

Decision Making Survival Analysis

Survival Seq2Seq: A Survival Model based on Sequence to Sequence Architecture

no code implementations • 9 Apr 2022 • Ebrahim Pourjafari, Navid Ziaei, Mohammad R. Rezaei, Amir Sameizadeh, Mohammad Shafiee, Mohammad Alavinia, Mansour Abolghasemian, Nick Sajadi

This paper introduces a novel non-parametric deep model for estimating time-to-event (survival analysis) in presence of censored data and competing risks.

Decoder Survival Analysis

A Deep-structured Conditional Random Field Model for Object Silhouette Tracking

no code implementations • 5 Jan 2015 • Mohammad Shafiee, Zohreh Azimifar, Alexander Wong

In this work, we introduce a deep-structured conditional random field (DS-CRF) model for the purpose of state-based object silhouette tracking.

Object Optical Flow Estimation