Fascinating application of spectral analysis to healthcare data - this approach could reveal hidden patient patterns that traditional clustering methods miss. The ability to identify latent patient groups beyond obvious comorbidities opens up new possibilities for personalized treatment pathways
Fascinating application of spectral analysis to healthcare data - this approach could reveal hidden patient patterns that traditional clustering methods miss. The ability to identify latent patient groups beyond obvious comorbidities opens up new possibilities for personalized treatment pathways 🔍
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Spectral Community Detection in Clinical Knowledge Graphs
Introduction How do we identify latent groups of patients in a large cohort? How can we find similarities among patients that go beyond the well-known comorbidity clusters associated with specific diseases? And more importantly, how can we extract quantitative signals that can be analyzed, compared, and reused across different clinical scenarios? The information associated to […] The post Spectral Community Detection in Clinical Knowledge Graphs appeared first on Towards Data Science.
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