{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,17]],"date-time":"2026-08-17T23:18:19Z","timestamp":1787008699845,"version":"build-2736575974"},"reference-count":35,"publisher":"Oxford University Press (OUP)","issue":"3","license":[{"start":{"date-parts":[[2021,7,1]],"date-time":"2021-07-01T00:00:00Z","timestamp":1625097600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"}],"funder":[{"DOI":"10.13039\/100000968","name":"American Heart Association","doi-asserted-by":"publisher","award":["#15GRNT23070001"],"award-info":[{"award-number":["#15GRNT23070001"]}],"id":[{"id":"10.13039\/100000968","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Institute of Precision Medicine","award":["17UNPG33840017"],"award-info":[{"award-number":["17UNPG33840017"]}]},{"name":"RICBAC Foundation"},{"DOI":"10.13039\/100000002","name":"National Institutes of Health","doi-asserted-by":"publisher","award":["1 R01 HL135335-01"],"award-info":[{"award-number":["1 R01 HL135335-01"]}],"id":[{"id":"10.13039\/100000002","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000002","name":"National Institutes of Health","doi-asserted-by":"publisher","award":["1 R21 HL137870-01"],"award-info":[{"award-number":["1 R21 HL137870-01"]}],"id":[{"id":"10.13039\/100000002","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000002","name":"National Institutes of Health","doi-asserted-by":"publisher","award":["1 R21 EB026164-01"],"award-info":[{"award-number":["1 R21 EB026164-01"]}],"id":[{"id":"10.13039\/100000002","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Founders Affiliate Post-doctoral Fellowship","award":["#19POST34450149"],"award-info":[{"award-number":["#19POST34450149"]}]},{"DOI":"10.13039\/100000968","name":"AHA","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100000968","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2021,9,30]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Aims<\/jats:title>\n                    <jats:p>This work attempts to develop a standalone heart rhythm alerting system for the intensive care unit (ICU), where life-threatening arrhythmias have to be identified\/alerted more precisely and more instantaneously (i.e. with lower latency) than existing bedside monitors.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods and results<\/jats:title>\n                    <jats:p>We use the dataset from the PhysioNet 2015 Challenge, which contains records that led to true and false arrhythmic alarms in the ICU. These records have been re-annotated as one of eight classes, namely (i) asystole, (ii) extreme bradycardia, (iii) extreme tachycardia, (iv) ventricular fibrillation (VF), (v) ventricular tachycardia (VT), (vi) normal sinus rhythm, (vii) sinus tachycardia, and (viii) noise\/artefacts. Arrhythmia-specific features and features that measure the signal quality were extracted from all the records. To improve VF detection, an improved, over an existing, single-lead R-wave detection was developed that takes into account the R-waves detected in all electrocardiographic (ECG) leads. To avoid false R-wave detection due to pacing spikes, ECG signals were filtered with a low pass filter prior to R-wave detection, while the raw signals were used for feature extraction. Random forest was used as the classifier, and 10-time five-fold cross-validation, resulted in a macro-average sensitivity of 81.54%.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>In conclusion, comparing with the bedside monitors used in the PhysioNet 2015 competition, we find that our method achieves higher positive predictive values for asystole, extreme bradycardia, VT, and VF; furthermore, our method is able to alert the presence of arrhythmia instantaneously, i.e. up to 4 s earlier.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1093\/ehjdh\/ztab058","type":"journal-article","created":{"date-parts":[[2021,7,1]],"date-time":"2021-07-01T09:55:42Z","timestamp":1625133342000},"page":"437-445","source":"Crossref","is-referenced-by-count":25,"title":["Real-time machine learning-based intensive care unit alarm classification without prior knowledge of the underlying rhythm"],"prefix":"10.1093","volume":"2","author":[{"given":"Wan-Tai M","family":"Au-Yeung","sequence":"first","affiliation":[{"name":"Cardiovascular Research Center, Massachusetts General Hospital , 149 13th St, Charlestown, MA 02129, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Rahul K","family":"Sevakula","sequence":"additional","affiliation":[{"name":"Cardiovascular Research Center, Massachusetts General Hospital , 149 13th St, Charlestown, MA 02129, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ashish K","family":"Sahani","sequence":"additional","affiliation":[{"name":"Center for Biomedical Engineering, Indian Institute of Technology Ropar , Rupnagar, Punjab 14001, India"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Mohamad","family":"Kassab","sequence":"additional","affiliation":[{"name":"Cardiovascular Research Center, Massachusetts General Hospital , 149 13th St, Charlestown, MA 02129, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Richard","family":"Boyer","sequence":"additional","affiliation":[{"name":"Anesthesia Department, Massachusetts General Hospital , 55 Fruit Street, Boston, MA 02114, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Eric M","family":"Isselbacher","sequence":"additional","affiliation":[{"name":"Healthcare Transformation Lab, Massachusetts General Hospital , 50 Staniford St, Boston, MA 02114, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Antonis A","family":"Armoundas","sequence":"additional","affiliation":[{"name":"Cardiovascular Research Center, Massachusetts General Hospital , 149 13th St, Charlestown, MA 02129, USA"},{"name":"Institute for Medical Engineering and Science, Massachusetts Institute of Technology , 45 Carleton St, Cambridge, MA 02142, 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