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Article

Unsupervised Agglomerative Cluster Phenotyping of Young Patients With Acute Coronary Syndrome Undergoing Percutaneous Coronary Intervention.

Catheterization and cardiovascular interventions : official journal of the Society for Cardiac Angiography & Interventions - 1 Jul 2026

Haisum Maqsood M, Chaaya Rody G Bou, Samimi Sahar, Hatab Taha, Qamar Fatima, Kharsa Chloe, Goel Sachin, Shah Alpesh R, Kleiman Neal S, Khan Safi U

Abstract excerpt

BACKGROUND: Young patients with acute coronary syndrome (ACS) exhibit diverse demographic, clinical and angiographic characteristics. We hypothesized that unsupervised machine learning (ML) can identify phenotypic clusters and predict the prognosis among young patients with ACS who undergo percutaneous coronary intervention (PCI). METHODS: We used the Houston Methodist Young-ACS PCI registry (2010-2022) and...

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PMID: 42026648
DOI: 10.1002/ccd.70643

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PubMed metadata and Literature Corpus relationships. Corpus snapshot updated 8 Sept 2026.

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