{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,23]],"date-time":"2026-10-23T05:59:00Z","timestamp":1792735140938,"version":"4.5.0"},"reference-count":65,"publisher":"MDPI AG","issue":"1","license":[{"start":{"date-parts":[[2023,12,27]],"date-time":"2023-12-27T00:00:00Z","timestamp":1703635200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100000780","name":"the European Union\u2019s Horizon 2020 research and innovation program TO_AITION","doi-asserted-by":"publisher","award":["848146"],"award-info":[{"award-number":["848146"]}],"id":[{"id":"10.13039\/501100000780","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Diagnostics"],"abstract":"<jats:p>Several studies have demonstrated a critical association between cardiovascular disease (CVD) and mental health, revealing that approximately one-third of individuals with CVD also experience depression. This comorbidity significantly increases the risk of cardiac complications and mortality, a risk that persists regardless of traditional factors. Addressing this issue, our study pioneers a straightforward, explainable, and data-driven pipeline for predicting depression in CVD patients. Methods: Our study was conducted at a cardiac surgical intensive care unit. A total of 224 participants who were scheduled for elective coronary artery bypass graft surgery (CABG) were enrolled in the study. Prior to surgery, each patient underwent psychiatric evaluation to identify major depressive disorder (MDD) based on the DSM-5 criteria. An advanced data curation workflow was applied to eliminate outliers and inconsistencies and improve data quality. An explainable AI-empowered pipeline was developed, where sophisticated machine learning techniques, including the AdaBoost, random forest, and XGBoost algorithms, were trained and tested on the curated data based on a stratified cross-validation approach. Results: Our findings identified a significant correlation between the biomarker \u201csRAGE\u201d and depression (r = 0.32, p = 0.038). Among the applied models, the random forest classifier demonstrated superior accuracy in predicting depression, with notable scores in accuracy (0.62), sensitivity (0.71), specificity (0.53), and area under the curve (0.67). Conclusions: This study provides compelling evidence that depression in CVD patients, particularly those with elevated \u201csRAGE\u201d levels, can be predicted with a 62% accuracy rate. Our AI-driven approach offers a promising way for early identification and intervention, potentially revolutionizing care strategies in this vulnerable population.<\/jats:p>","DOI":"10.3390\/diagnostics14010067","type":"journal-article","created":{"date-parts":[[2023,12,27]],"date-time":"2023-12-27T05:43:15Z","timestamp":1703655795000},"page":"67","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":22,"title":["AI-Enhanced Predictive Modeling for Identifying Depression and Delirium in Cardiovascular Patients Scheduled for Cardiac Surgery"],"prefix":"10.3390","volume":"14","author":[{"given":"Karina","family":"Nowakowska","sequence":"first","affiliation":[{"name":"Department of Old Age Psychiatry and Psychotic Disorders, Medical University of Lodz, 90-419 Lodz, Poland"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Antonis","family":"Sakellarios","sequence":"additional","affiliation":[{"name":"Laboratory of Biomechanics and Biomedical Engineering, Department of Mechanical and Aeronautics Engineering, University of Patras, 26504 Patras, Greece"},{"name":"Unit of Medical Technology and Intelligent Information Systems, Department of Materials Science and Engineering, University of Ioannina, 45110 Ioannina, Greece"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6002-7123","authenticated-orcid":false,"given":"Jakub","family":"Ka\u017amierski","sequence":"additional","affiliation":[{"name":"Department of Old Age Psychiatry and Psychotic Disorders, Medical University of Lodz, 90-419 Lodz, Poland"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7362-5082","authenticated-orcid":false,"given":"Dimitrios I.","family":"Fotiadis","sequence":"additional","affiliation":[{"name":"Unit of Medical Technology and Intelligent Information Systems, Department of Materials Science and Engineering, University of Ioannina, 45110 Ioannina, Greece"},{"name":"Biomedical Research Institute\u2014FORTH, University Campus of Ioannina, 45110 Ioannina, Greece"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Vasileios C.","family":"Pezoulas","sequence":"additional","affiliation":[{"name":"Unit of Medical Technology and Intelligent Information Systems, Department of Materials Science and Engineering, University of Ioannina, 45110 Ioannina, Greece"},{"name":"Biomedical Research Institute\u2014FORTH, University Campus of Ioannina, 45110 Ioannina, Greece"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2023,12,27]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"e146","DOI":"10.1161\/CIR.0000000000000485","article-title":"Heart Disease and Stroke Statistics-2017 Update: A Report From the American Heart Association","volume":"135","author":"Benjamin","year":"2017","journal-title":"Circulation"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"1789","DOI":"10.1016\/S0140-6736(18)32279-7","article-title":"Global, Regional, and National Incidence, Prevalence, and Years Lived with Disability for 354 Diseases and Injuries for 195 Countries and Territories, 1990\u20132017: A Systematic Analysis for the Global Burden of Disease Study 2017","volume":"392","author":"James","year":"2018","journal-title":"Lancet"},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"11","DOI":"10.1016\/j.jad.2019.08.081","article-title":"Associations of Cardiovascular Disease and Depression with Memory Related Disease: A Chinese National Prospective Cohort Study","volume":"260","author":"Xue","year":"2020","journal-title":"J. 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