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Inferring Disease Status by Non-parametric Probabilistic Embedding
[chapter]
2017
Lecture Notes in Computer Science
Computing similarity between all pairs of patients in a dataset enables us to group the subjects into disease subtypes and infer their disease status. However, robust and efficient computation of pairwise similarity is a challenging task for large-scale medical image datasets. We specifically target diseases where multiple subtypes of pathology present simultaneously, rendering the definition of the similarity a difficult task. To define pairwise patient similarity, we characterize each subject
doi:10.1007/978-3-319-61188-4_5
fatcat:gjy5pqnrqzanjcajwko77ikspa