Time-to-event prediction using survival analysis methods for Alzheimer's disease progression.

ABSTRACT:

Introduction

Many research studies have well investigated Alzheimer's disease (AD) detection and progression. However, the continuous-time survival prediction of AD is not yet fully explored to support medical practitioners with predictive analytics. In this study, we develop a survival analysis approach to examine interactions between patients' inherent temporal and medical patterns and predict the probability of the AD next stage progression during a time period. The likelihood of reaching the following AD stage is unique to a patient, helping the medical practitioner analyze the patient's condition and provide personalized treatment recommendations ahead of time.

Methodologies

We simulate the disease progression based on patient profiles using non-linear survival methods-

SUBMITTER: Sharma R 

PROVIDER: S-EPMC8719343 | biostudies-literature | 2021

REPOSITORIES: biostudies-literature