Clustering Patients with Tensor Decomposition
This addresses clustering patient records for healthcare applications, but appears incremental as it adapts tensor decomposition to this domain.
The paper tackled unsupervised clustering of high-dimensional binary data, specifically electronic healthcare records, using tensor decomposition, and obtained clinically meaningful results on two datasets.
In this paper we present a method for the unsupervised clustering of high-dimensional binary data, with a special focus on electronic healthcare records. We present a robust and efficient heuristic to face this problem using tensor decomposition. We present the reasons why this approach is preferable for tasks such as clustering patient records, to more commonly used distance-based methods. We run the algorithm on two datasets of healthcare records, obtaining clinically meaningful results.