# Clustering Patients with Tensor Decomposition

arXiv: https://arxiv.org/abs/1708.08994 · HTML: https://mlsanity.com/paper/1708.08994/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 29 Aug 2017.

## Built on by (most cited first, 2 of 2)

- [Tensor decomposition for learning Gaussian mixtures from moments](https://mlsanity.com/paper/2106.00555/) (2021)
- [Individualized Context-Aware Tensor Factorization for Online Games Predictions](https://mlsanity.com/paper/2102.11352/) (2021)

## Abstract (arXiv)

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.