UNASSIGNED: @entity746 ( @entity746 ) is a progressive @entity4094 , with large variation in survival between @entity1 . 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 @entity746 @entity1 using deep learning, a machine learning technique highly effective in a broad range of big-data analyses. A group of 135 @entity746 @entity1 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 @entity1 was monitored carefully and survival time to @entity204 was recorded. @entity1 were labeled as short, medium or long survivors, based on their recorded time to @entity204 as measured from the time of disease onset. In the deep learning procedure, the total group of 135 @entity1 was split into a training set for deep learning (n  =  83 @entity1 ), a validation set (n  =  20) and an independent evaluation set (n  =  32) to evaluate the performance of the obtained deep learning networks. Deep learning based on clinical characteristics predicted survival category correctly in 68.8% of the cases. Deep learning based on MRI predicted 62.5% correctly using structural connectivity and 62.5% using brain morphology data. Notably, when we combined the three sources of information, deep learning prediction accuracy increased to 84.4%. Taken together, our findings show the added value of MRI with respect to predicting survival in @entity746 , demonstrating the advantage of deep learning in disease prognostication.

Deep learning predictions of survival based on MRI in XXXX .

@entity1 :: ('9606', 'Species') :: ['Patients', 'patients'] @entity4094 :: ('MESH:D009468', 'Disease') :: ['neuromuscular disease'] @entity204 :: ('MESH:D003643', 'Disease') :: ['death'] @entity746 :: ('MESH:D000690', 'Disease') :: ['ALS', 'Amyotrophic lateral sclerosis']
@entity746 :: (MESH:D000690,Disease) :: ['amyotrophic lateral sclerosis']
