Deep learning predictions of survival based on MRI in amyotrophic lateral sclerosis.

ABSTRACT: Amyotrophic lateral sclerosis (ALS) is a progressive neuromuscular disease, with large variation in survival between patients. Currently, it remains rather difficult to predict survival based on clinical parameters alone. Here, we set out to use clinical characteristics in combination with MRI data to predict survival of ALS patients using deep learning, a machine learning technique highly effective in a broad range of big-data analyses. A group of 135 ALS patients was included from whom high-resolution diffusion-weighted and T1-weighted images were acquired at the first visit to the outpatient clinic. Next, each of the patients was monitored carefully and survival time to death was recorded. Patients were labeled as short, medium or long survivors, based on their recorded time to death as

SUBMITTER: van der Burgh HK 

PROVIDER: S-EPMC5219634 | biostudies-literature | 2017

REPOSITORIES: biostudies-literature