{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,19]],"date-time":"2026-08-19T15:26:15Z","timestamp":1787153175740,"version":"build-2736575974"},"reference-count":15,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2026,8,19]],"date-time":"2026-08-19T00:00:00Z","timestamp":1787097600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["frontiersin.org"],"crossmark-restriction":true},"short-container-title":["Front. Artif. Intell."],"abstract":"<jats:sec>\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>Current classification of Acute Myocardial Infarction (AMI) into ST-elevation (STEMI) and non-ST-elevation (NSTEMI) myocardial infarction does not fully reflect the clinical heterogeneity of patients.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Objectives<\/jats:title>\n                    <jats:p>To identify clinically meaningful phenotypes of AMI patients using an unsupervised clustering approach and assess their associations with management strategies and long-term outcomes.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>Hierarchical agglomerative clustering using Ward\u2019s method was performed in 4,947 patients from the French FAST-MI 2015 nationwide registry. Clustering was based on baseline clinical, demographic, and laboratory features. Between-cluster differences in baseline characteristics, management, in-hospital complications, and 1-year mortality were analyzed.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>\n                      Four phenotypic clusters were identified. Cluster 1 (n\u202f=\u202f1,488) gathered older patients, predominantly men, with typical coronary risk factors, intermediate risk profile, and balanced STEMI\/NSTEMI presentations. Cluster 2 (\n                      <jats:italic>n<\/jats:italic>\n                      \u202f=\u202f1,305) gathered older polymorbid patients, 45% were women, 60% with NSTEMI presentation, with limited use of invasive strategies (71%), and a high 1-year mortality. Cluster 3 (n\u202f=\u202f815) gathered young (mean age 44\u202fyears), predominantly male patients, with a high prevalence of smoking (73%) and few comorbidities, 62% STEMI, high rates of revascularization, and excellent prognosis. Cluster 4 (\n                      <jats:italic>n<\/jats:italic>\n                      \u202f=\u202f1,339) was close to Cluster 3 with a more metabolic profile with higher rates of obesity, diabetes, and dyslipidemia, also with favorable outcomes. In-hospital complications were more frequent in Clusters 1 and 2. One-year mortality was lowest in Clusters 3 and 4 (1.5 and 2.3%), intermediate in Cluster 1 (6.0%), and highest in Cluster 2 (15.7%).\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion<\/jats:title>\n                    <jats:p>Unsupervised clustering identified four clinically relevant AMI phenotypes with distinct characteristics, management patterns, and prognoses. This data-driven classification highlights the diversity of AMI presentations and may offer complementary insights for patient profiling and risk stratification.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.3389\/frai.2026.1886402","type":"journal-article","created":{"date-parts":[[2026,8,19]],"date-time":"2026-08-19T14:46:40Z","timestamp":1787150800000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["Unsupervised clustering identifies distinct phenotypes in acute myocardial infarction: insights from the FAST-MI 2015 registry"],"prefix":"10.3389","volume":"9","author":[{"given":"Vincent","family":"Bataille","sequence":"first","affiliation":[{"name":"INSERM UMR 1295, CERPOP, Toulouse Rangueil University Hospital, Toulouse University School of Medicine","place":["Toulouse, France"]},{"name":"ADIMEP (Association pour la Diffusion de la M\u00e9decine de Pr\u00e9vention)","place":["Toulouse, France"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Lo\u00efc","family":"Panh","sequence":"additional","affiliation":[{"name":"Department of Cardiology, Clinique Pasteur","place":["Toulouse, France"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Etienne","family":"Puymirat","sequence":"additional","affiliation":[{"name":"Department of Cardiology, Assistance Publique-H\u00f4pitaux de Paris (AP-HP), H\u00f4pital Europ\u00e9en Georges Pompidou","place":["Paris, France"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Guillaume","family":"Cayla","sequence":"additional","affiliation":[{"name":"Department of Cardiology, University Hospital of N\u00eemes, University of Montpellier","place":["N\u00eemes, France"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Pascal","family":"Motreff","sequence":"additional","affiliation":[{"name":"Department of Cardiology, University Hospital of Clermont-Ferrand","place":["Clermont-Ferrand, France"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Gilles","family":"Lemesle","sequence":"additional","affiliation":[{"name":"Department of Cardiology, Heart and Lung Institute, University Hospital of Lille","place":["Lille, France"]},{"name":"French Alliance for Cardiovascular Trials (FACT)","place":["Paris, France"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Fran\u00e7ois","family":"Schiele","sequence":"additional","affiliation":[{"name":"Department of Cardiology, University Hospital of Besan\u00e7on, University of Franche Comte, SINERGIES","place":["Besan\u00e7on, France"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Tabassome","family":"Simon","sequence":"additional","affiliation":[{"name":"Department of Clinical Pharmacology, H\u00f4pital Saint-Antoine, Assistance Publique-H\u00f4pitaux de Paris (AP-HP)","place":["Paris, France"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Nicolas","family":"Danchin","sequence":"additional","affiliation":[{"name":"French Alliance for Cardiovascular Trials (FACT)","place":["Paris, France"]},{"name":"Department of Cardiology, H\u00f4pital Saint Joseph","place":["Paris, France"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jean","family":"Ferri\u00e8res","sequence":"additional","affiliation":[{"name":"INSERM UMR 1295, CERPOP, Toulouse Rangueil University Hospital, Toulouse University School of Medicine","place":["Toulouse, France"]},{"name":"Department of Cardiology, Toulouse Rangueil University Hospital","place":["Toulouse, France"]}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1965","published-online":{"date-parts":[[2026,8,19]]},"reference":[{"key":"ref1","doi-asserted-by":"publisher","first-page":"85","DOI":"10.1186\/s12916-021-01940-7","article-title":"Machine learning for subtype definition and risk prediction in heart failure, acute coronary syndromes and atrial fibrillation: systematic review of validity and clinical utility","volume":"19","author":"Banerjee","year":"2021","journal-title":"BMC Med."},{"key":"ref2","doi-asserted-by":"publisher","first-page":"1291","DOI":"10.1016\/j.jacc.2021.07.039","article-title":"Percutaneous myocardial revascularization in late-presenting patients with STEMI","volume":"78","author":"Bouisset","year":"2021","journal-title":"J. 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