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Model inputs included sex, age, ECG and the first blood tests at patient presentation: High sensitivity TnT (hs-cTnT), glucose, creatinine, and hemoglobin. For a safe rule-out, the models were adapted to achieve a sensitivity\u2009&gt;\u200999% and a negative predictive value (NPV)\u2009&gt;\u200999.5% for 30-day AMI\/death. For rule-in, we set the models to achieve a specificity\u2009&gt;\u200990% and a positive predictive value (PPV) of\u2009&gt;\u200970%. The models were also compared with the 0\u00a0h arm of the European Society of Cardiology algorithm (ESC 0\u00a0h); An initial hs-cTnT\u2009&lt;\u20095\u00a0ng\/L for rule-out and\u2009\u2265\u200952\u00a0ng\/L for rule-in. A convolutional neural network was the best model and identified 55% of the patients for rule-out and 5.3% for rule-in, while maintaining the required sensitivity, specificity, NPV and PPV levels. ESC 0\u00a0h failed to reach these performance levels.<\/jats:p>\n              <\/jats:sec><jats:sec>\n                <jats:title>Discussion<\/jats:title>\n                <jats:p>An ML model based on age, sex, ECG and blood tests at ED arrival can identify six out of ten chest pain patients for safe early rule-out or rule-in with no need for serial blood tests. Future studies should attempt to improve these ML models further, e.g. by including additional input data.<\/jats:p>\n              <\/jats:sec>","DOI":"10.1186\/s12911-023-02119-1","type":"journal-article","created":{"date-parts":[[2023,2,2]],"date-time":"2023-02-02T16:34:48Z","timestamp":1675355688000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":19,"title":["Machine learning for early prediction of acute myocardial infarction or death in acute chest pain patients using electrocardiogram and blood tests at presentation"],"prefix":"10.1186","volume":"23","author":[{"given":"Pontus Olsson","family":"de Capretz","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Anders","family":"Bj\u00f6rkelund","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jonas","family":"Bj\u00f6rk","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Mattias","family":"Ohlsson","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Arash","family":"Mokhtari","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Axel","family":"Nystr\u00f6m","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ulf","family":"Ekelund","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2023,2,2]]},"reference":[{"issue":"10","key":"2119_CR1","doi-asserted-by":"publisher","first-page":"979","DOI":"10.1111\/j.1553-2712.1999.tb01177.x","volume":"6","author":"JE Hollander","year":"1999","unstructured":"Hollander JE. 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All methods were carried out in accordance with relevant guidelines and regulations. Active consent was waived by the Regional Ethics Review Board in Lund, Sweden (Dnr 2018-708) and the Swedish Ethics Review Authority (Dnr 2019-03523), but patients were informed about the study and had the option to decline participation at any time, for any reason.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Ethics approval and consent to participate"}},{"value":"Not applicable.","order":3,"name":"Ethics","group":{"name":"EthicsHeading","label":"Consent for publication"}},{"value":"The authors declare that they have no competing interests.","order":4,"name":"Ethics","group":{"name":"EthicsHeading","label":"Competing interests"}}],"article-number":"25"}}