Factor enhanced DeepSurv: A deep learning approach for predicting survival probabilities in cirrhosis data.

Journal: Computers in biology and medicine
PMID:

Abstract

BACKGROUND: Over the years, various models, including both traditional and machine learning models, have been employed to predict survival probabilities for diverse survival datasets. The objective is to obtain models that provide more accurate estimates of survival probabilities. Certain datasets exhibit complex nonlinear effects and interactions between variables that may necessitate the application of deep learning algorithms to comprehend the underlying data generation process.

Authors

  • Chukwudi Paul Obite
    School of Mathematical and Statistical Sciences, Arizona State University, USA. Electronic address: cobite@asu.edu.
  • Emmanuella Onyinyechi Chukwudi
    Department of Statistics, Federal University of Technology, Owerri, Nigeria.
  • Merit Uchechukwu
    Department of Statistics, Federal University of Technology, Owerri, Nigeria.
  • Ugochinyere Ihuoma Nwosu
    Department of Statistics, Federal University of Technology, Owerri, Nigeria; Department of Computing and Mathematics, Manchester Metropolitan University, UK.