This case-study examines the patterns, symmetries, associations and causality in a rare but devastating disease, amyotrophic lateral sclerosis (ALS). A major clinically relevant question in this biomedical study is: What patient phenotypes can be automatically and reliably identified and used to predict the change of the ALSFRS slope over time?. This problem aims to explore the data set by unsupervised learning.
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