Patient Clustering via Integrated Profiling of Clinical and Digital Data
- URL: http://arxiv.org/abs/2308.11748v1
- Date: Tue, 22 Aug 2023 19:25:04 GMT
- Title: Patient Clustering via Integrated Profiling of Clinical and Digital Data
- Authors: Dongjin Choi, Andy Xiang, Ozgur Ozturk, Deep Shrestha, Barry Drake,
Hamid Haidarian, Faizan Javed, Haesun Park
- Abstract summary: We introduce a novel profile-based patient clustering model designed for clinical data in healthcare.
Our model takes advantage of patients' clinical data and digital interaction data, including browsing and search, to construct patient profiles.
- Score: 2.370296071691569
- License: http://creativecommons.org/licenses/by/4.0/
- Abstract: We introduce a novel profile-based patient clustering model designed for
clinical data in healthcare. By utilizing a method grounded on constrained
low-rank approximation, our model takes advantage of patients' clinical data
and digital interaction data, including browsing and search, to construct
patient profiles. As a result of the method, nonnegative embedding vectors are
generated, serving as a low-dimensional representation of the patients. Our
model was assessed using real-world patient data from a healthcare web portal,
with a comprehensive evaluation approach which considered clustering and
recommendation capabilities. In comparison to other baselines, our approach
demonstrated superior performance in terms of clustering coherence and
recommendation accuracy.
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