{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,24]],"date-time":"2026-10-24T08:04:51Z","timestamp":1792829091472,"version":"4.5.0"},"reference-count":109,"publisher":"MDPI AG","issue":"23","license":[{"start":{"date-parts":[[2025,11,27]],"date-time":"2025-11-27T00:00:00Z","timestamp":1764201600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["JCM"],"abstract":"<jats:p>Acute Aortic Syndromes (AAS) and Thoracic Aortic Aneurysm (TAA) remain among the most fatal cardiovascular emergencies, with mortality rising by the hour if diagnosis and treatment are delayed. Despite advances in imaging and surgical techniques, current clinical decision-making still relies heavily on population-based parameters such as maximum aortic diameter, which fail to capture the biological and biomechanical complexity underlying these conditions. In today\u2019s data-rich era, where vast clinical, imaging, and biomarker datasets are available, artificial intelligence (AI) has emerged as a powerful tool to process this complexity and enable precision risk prediction. To date, AI has been applied across multiple aspects of aortic disease management, with mortality prediction being the most widely investigated. Machine learning (ML) and deep learning (DL) models\u2014particularly ensemble algorithms and biomarker-integrated approaches\u2014have frequently outperformed traditional clinical tools such as EuroSCORE II and GERAADA. These models provide superior discrimination and interpretability, identifying key drivers of adverse outcomes. However, many studies remain limited by small sample sizes, single-center design, and lack of external validation, all of which constrain their generalizability. Despite these challenges, the consistently strong results highlight AI\u2019s growing potential to complement and enhance existing prognostic frameworks. Beyond mortality, AI has expanded the scope of analysis to the structural and biomechanical behavior of the aorta itself. Through integration of imaging, radiomic, and computational modeling data, AI now allows virtual representation of aortic mechanics\u2014enabling prediction of aneurysm growth rate, remodeling after repair, and even rupture risk and location. Such models bridge data-driven learning with mechanistic understanding, creating an opportunity to simulate disease progression in a virtual environment. In addition to mortality and growth-related outcomes, morbidity prediction has become another area of rapid development. AI models have been used to assess a wide range of postoperative complications, including stroke, gastrointestinal bleeding, prolonged hospitalization, reintubation, and paraplegia\u2014showing that predictive applications are limited only by clinical imagination. Among these, acute kidney injury (AKI) has received particular attention, with several robust studies demonstrating high accuracy in early identification of patients at risk for severe renal complications. To translate these promising results into real-world clinical use, future work must focus on large multicenter collaborations, external validation, and adherence to transparent reporting standards such as TRIPOD-AI. Integration of explainable AI frameworks and dynamic, patient-specific modeling\u2014potentially through the development of digital twins\u2014will be essential for achieving real-time clinical applicability. Ultimately, AI holds the potential not only to refine risk prediction but to fundamentally transform how we understand, monitor, and manage patients with AAS and TAA.<\/jats:p>","DOI":"10.3390\/jcm14238420","type":"journal-article","created":{"date-parts":[[2025,11,28]],"date-time":"2025-11-28T11:19:51Z","timestamp":1764328791000},"page":"8420","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":9,"title":["Applications of Artificial Intelligence as a Prognostic Tool in the Management of Acute Aortic Syndrome and Aneurysm: A Comprehensive Review"],"prefix":"10.3390","volume":"14","author":[{"given":"Cagri","family":"Ayhan","sequence":"first","affiliation":[{"name":"Royal College of Surgeons in Ireland (RCSI), University of Medicine and Health Sciences, D02 YN77 Dublin, Ireland"},{"name":"Precision Cardiovascular Medicine & Innovation Institute (PCMI), Cardiovascular Research Institute Dublin (CVRI), Mater Private Network, D07 KWR1 Dublin, Ireland"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Marina","family":"Mekhaeil","sequence":"additional","affiliation":[{"name":"School of Medicine, University of Galway, H91 TK33 Galway, Ireland"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Rita","family":"Channawi","sequence":"additional","affiliation":[{"name":"School of Medicine, University of Galway, H91 TK33 Galway, Ireland"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Alp Eren","family":"Ozcan","sequence":"additional","affiliation":[{"name":"School of Medicine, University of Duzce, 81620 Duzce, Turkey"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Elif","family":"Akargul","sequence":"additional","affiliation":[{"name":"Department of Aerospace Medicine, Gulhane Faculty of Medicine, Saglik Bilimleri University, 34480 Istanbul, Turkey"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0007-4995-6379","authenticated-orcid":false,"given":"Atakan","family":"Deger","sequence":"additional","affiliation":[{"name":"School of Medicine, Atilim University, 06830 Ankara, Turkey"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0003-2967-1668","authenticated-orcid":false,"given":"Incilay","family":"Cayan","sequence":"additional","affiliation":[{"name":"School of Medicine, Atilim University, 06830 Ankara, Turkey"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0007-4557-0372","authenticated-orcid":false,"given":"Amr","family":"Abdalla","sequence":"additional","affiliation":[{"name":"School of Medicine, University of Galway, H91 TK33 Galway, Ireland"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0001-8227-9628","authenticated-orcid":false,"given":"Christopher","family":"Chan","sequence":"additional","affiliation":[{"name":"School of Medicine, University of Galway, H91 TK33 Galway, Ireland"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ronan","family":"Mahon","sequence":"additional","affiliation":[{"name":"School of Medicine, University of Galway, H91 TK33 Galway, Ireland"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Dilara","family":"Ayhan","sequence":"additional","affiliation":[{"name":"University Hospital Limerick, V94 F858 Limerick, Ireland"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"William","family":"Wijns","sequence":"additional","affiliation":[{"name":"The Lambe Institute for Translational Medicine and C\u00daRAM, National University of Ireland Galway, H91 TK33 Galway, Ireland"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Sherif","family":"Sultan","sequence":"additional","affiliation":[{"name":"Western Vascular Institute, Department of Vascular and Endovascular Surgery, University Hospital Galway, University of Galway, H91 TK33 Galway, Ireland"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0758-3539","authenticated-orcid":false,"given":"Osama","family":"Soliman","sequence":"additional","affiliation":[{"name":"Royal College of Surgeons in Ireland (RCSI), University of Medicine and Health Sciences, D02 YN77 Dublin, Ireland"},{"name":"Precision Cardiovascular Medicine & Innovation Institute (PCMI), Cardiovascular Research Institute Dublin (CVRI), Mater Private Network, D07 KWR1 Dublin, Ireland"},{"name":"The Euro Heart Foundation, 3071 EG Rotterdam, The Netherlands"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2025,11,27]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"305","DOI":"10.1136\/pgmj.2005.043083","article-title":"Acute aortic syndrome: Pathology and therapeutic strategies","volume":"82","author":"Ahmad","year":"2006","journal-title":"Postgrad Med. 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