{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,12,17]],"date-time":"2025-12-17T18:09:49Z","timestamp":1765994989985,"version":"3.37.3"},"reference-count":26,"publisher":"Springer Science and Business Media LLC","issue":"7","license":[{"start":{"date-parts":[[2022,6,8]],"date-time":"2022-06-08T00:00:00Z","timestamp":1654646400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2022,6,8]],"date-time":"2022-06-08T00:00:00Z","timestamp":1654646400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["J Med Syst"],"published-print":{"date-parts":[[2022,7]]},"DOI":"10.1007\/s10916-022-01833-z","type":"journal-article","created":{"date-parts":[[2022,6,8]],"date-time":"2022-06-08T02:03:08Z","timestamp":1654653788000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":13,"title":["Pilot Report for Intracranial Hemorrhage Detection with Deep Learning Implanted Head Computed Tomography Images at Emergency Department"],"prefix":"10.1007","volume":"46","author":[{"given":"Hung-Wei Chang","family":"Chien","sequence":"first","affiliation":[]},{"given":"Tsung-Lung","family":"Yang","sequence":"additional","affiliation":[]},{"given":"Wang-Chuan","family":"Juang","sequence":"additional","affiliation":[]},{"given":"Yen-Yu Arthur","family":"Chen","sequence":"additional","affiliation":[]},{"given":"Yu-Chuan Jack","family":"Li","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5508-7647","authenticated-orcid":false,"given":"Chih-Yu","family":"Chen","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2022,6,8]]},"reference":[{"key":"1833_CR1","doi-asserted-by":"crossref","unstructured":"Majumdar A, Brattain L, Telfer B, Farris C, Scalera J: Detecting intracranial hemorrhage with deep learning. In: 2018 40th annual international conference of the IEEE engineering in medicine and biology society (EMBC): 2018: IEEE; 2018: 583\u2013587.","DOI":"10.1109\/EMBC.2018.8512336"},{"issue":"7","key":"1833_CR2","doi-asserted-by":"publisher","first-page":"2032","DOI":"10.1161\/STR.0000000000000069","volume":"46","author":"JC Hemphill III","year":"2015","unstructured":"Hemphill III JC, Greenberg SM, Anderson CS, Becker K, Bendok BR, Cushman M, Fung GL, Goldstein JN, Macdonald RL, Mitchell PH: Guidelines for the management of spontaneous intracerebral hemorrhage: a guideline for healthcare professionals from the American Heart Association\/American Stroke Association. Stroke 2015, 46(7):2032-2060.","journal-title":"Stroke"},{"issue":"9675","key":"1833_CR3","doi-asserted-by":"publisher","first-page":"1632","DOI":"10.1016\/S0140-6736(09)60371-8","volume":"373","author":"AI Qureshi","year":"2009","unstructured":"Qureshi AI, Mendelow AD, Hanley DF: Intracerebral haemorrhage. The Lancet 2009, 373(9675):1632-1644.","journal-title":"The Lancet"},{"issue":"5","key":"1833_CR4","doi-asserted-by":"publisher","first-page":"1646","DOI":"10.1109\/JBHI.2020.3028243","volume":"25","author":"L Li","year":"2020","unstructured":"Li L, Wei M, Liu B, Atchaneeyasakul K, Zhou F, Pan Z, Kumar SA, Zhang JY, Pu Y, Liebeskind DS: Deep learning for hemorrhagic lesion detection and segmentation on brain ct images. IEEE Journal of Biomedical and Health Informatics 2020, 25(5):1646-1659.","journal-title":"IEEE Journal of Biomedical and Health Informatics"},{"issue":"1","key":"1833_CR5","first-page":"50","volume":"108","author":"MM Rymer","year":"2011","unstructured":"Rymer MM: Hemorrhagic stroke: intracerebral hemorrhage. Missouri medicine 2011, 108(1):50.","journal-title":"Missouri medicine"},{"issue":"3","key":"1833_CR6","doi-asserted-by":"publisher","first-page":"143","DOI":"10.1159\/000441082","volume":"45","author":"GA Mensah","year":"2015","unstructured":"Mensah GA, Norrving B, Feigin VL: The global burden of stroke. Neuroepidemiology 2015, 45(3):143-145.","journal-title":"Neuroepidemiology"},{"issue":"1","key":"1833_CR7","doi-asserted-by":"publisher","first-page":"95","DOI":"10.1016\/j.ehmc.2016.08.002","volume":"6","author":"JA Carter","year":"2017","unstructured":"Carter JA, Curry W: Intracerebral hemorrhage: pathophysiology and management for generalists. Hospital Medicine Clinics 2017, 6(1):95-111.","journal-title":"Hospital Medicine Clinics"},{"issue":"3","key":"1833_CR8","doi-asserted-by":"publisher","first-page":"335","DOI":"10.1007\/s00234-019-02330-w","volume":"62","author":"DT Ginat","year":"2020","unstructured":"Ginat DT: Analysis of head CT scans flagged by deep learning software for acute intracranial hemorrhage. Neuroradiology 2020, 62(3):335-340.","journal-title":"Neuroradiology"},{"key":"1833_CR9","doi-asserted-by":"crossref","unstructured":"Expert Panel on Neurologic I, Salmela MB, Mortazavi S, Jagadeesan BD, Broderick DF, Burns J, Deshmukh TK, Harvey HB, Hoang J, Hunt CH et al: ACR Appropriateness Criteria((R)) Cerebrovascular Disease. J Am Coll Radiol 2017, 14(5S):S34-S61.","DOI":"10.1016\/j.jacr.2017.01.051"},{"issue":"9","key":"1833_CR10","doi-asserted-by":"publisher","first-page":"1191","DOI":"10.1016\/j.acra.2015.05.007","volume":"22","author":"RJ McDonald","year":"2015","unstructured":"McDonald RJ, Schwartz KM, Eckel LJ, Diehn FE, Hunt CH, Bartholmai BJ, Erickson BJ, Kallmes DF: The effects of changes in utilization and technological advancements of cross-sectional imaging on radiologist workload. Academic radiology 2015, 22(9):1191-1198.","journal-title":"Academic radiology"},{"issue":"8","key":"1833_CR11","doi-asserted-by":"publisher","first-page":"2573","DOI":"10.1161\/STROKEAHA.119.027479","volume":"51","author":"K Mouridsen","year":"2020","unstructured":"Mouridsen K, Thurner P, Zaharchuk G: Artificial intelligence applications in stroke. Stroke 2020, 51(8):2573-2579.","journal-title":"Stroke"},{"key":"1833_CR12","doi-asserted-by":"publisher","first-page":"60","DOI":"10.1016\/j.media.2017.07.005","volume":"42","author":"G Litjens","year":"2017","unstructured":"Litjens G, Kooi T, Bejnordi BE, Setio AAA, Ciompi F, Ghafoorian M, Van Der Laak JA, Van Ginneken B, S\u00e1nchez CI: A survey on deep learning in medical image analysis. Medical image analysis 2017, 42:60-88.","journal-title":"Medical image analysis"},{"issue":"11","key":"1833_CR13","doi-asserted-by":"publisher","first-page":"e24163","DOI":"10.2196\/24163","volume":"8","author":"MM Islam","year":"2020","unstructured":"Islam MM, Yang H-C, Poly TN, Li Y-CJ: Development of an artificial intelligence\u2013based automated recommendation system for clinical laboratory tests: Retrospective analysis of the national health insurance database. JMIR medical informatics 2020, 8(11):e24163.","journal-title":"JMIR medical informatics"},{"key":"1833_CR14","doi-asserted-by":"crossref","unstructured":"Xu Y, Holanda G, Fabr\u00edcio L, de F S, Silva H, Gomes A, Silva I, Ferreira M, Jia C, Han T: Deep learning-enhanced Internet of medical things to analyze brain CT scans of hemorrhagic stroke patients: A new approach. IEEE Sensors Journal 2020.","DOI":"10.1109\/JSEN.2020.3032897"},{"issue":"9","key":"1833_CR15","doi-asserted-by":"publisher","first-page":"1527","DOI":"10.1001\/jamainternmed.2015.3540","volume":"175","author":"AW Hsing","year":"2015","unstructured":"Hsing AW, Ioannidis JPA: Nationwide Population Science: Lessons From the Taiwan National Health Insurance Research Database. JAMA Internal Medicine 2015, 175(9):1527-1529.","journal-title":"JAMA Internal Medicine"},{"issue":"14","key":"1833_CR16","doi-asserted-by":"publisher","first-page":"1341","DOI":"10.1001\/jama.2020.3151","volume":"323","author":"CJ Wang","year":"2020","unstructured":"Wang CJ, Ng CY, Brook RH: Response to COVID-19 in Taiwan: Big Data Analytics, New Technology, and Proactive Testing. JAMA 2020, 323(14):1341-1342.","journal-title":"JAMA"},{"issue":"6","key":"1833_CR17","doi-asserted-by":"publisher","first-page":"861","DOI":"10.1093\/intqhc\/mzx123","volume":"29","author":"C-Y Tsai","year":"2017","unstructured":"Tsai C-Y, Yang H-C, Islam M, Hsieh W-S, Juan S-H, Chen J-C, Khan HAA, Jian W-S: Psychotropic medications prescribing trends in adolescents: A nationwide population-based study in Taiwan. International Journal for Quality in Health Care 2017, 29(6):861-866.","journal-title":"International Journal for Quality in Health Care"},{"key":"1833_CR18","unstructured":"Wang H-C, Chou J-H, Chiu W-T, Nien H-C, Jr. JL: Validation of a deep learning algorithm to detect acute intracranial hemorrhage on non-contrast brain CT. In: 2nd International Conference of AI in Healthcare (ICAIH). Los Angeles, CA; 2019."},{"issue":"45","key":"1833_CR19","doi-asserted-by":"publisher","first-page":"22737","DOI":"10.1073\/pnas.1908021116","volume":"116","author":"W Kuo","year":"2019","unstructured":"Kuo W, H\u04d3ne C, Mukherjee P, Malik J, Yuh EL: Expert-level detection of acute intracranial hemorrhage on head computed tomography using deep learning. Proceedings of the National Academy of Sciences 2019, 116(45):22737-22745.","journal-title":"Proceedings of the National Academy of Sciences"},{"issue":"8","key":"1833_CR20","doi-asserted-by":"publisher","first-page":"e0203316","DOI":"10.1371\/journal.pone.0203316","volume":"13","author":"C Morley","year":"2018","unstructured":"Morley C, Unwin M, Peterson GM, Stankovich J, Kinsman L: Emergency department crowding: a systematic review of causes, consequences and solutions. PloS one 2018, 13(8):e0203316.","journal-title":"PloS one"},{"issue":"4","key":"1833_CR21","doi-asserted-by":"publisher","first-page":"553","DOI":"10.5811\/westjem.2017.4.32740","volume":"18","author":"KE Schreyer","year":"2017","unstructured":"Schreyer KE, Martin R: The economics of an admissions holding unit. Western Journal of Emergency Medicine 2017, 18(4):553.","journal-title":"Western Journal of Emergency Medicine"},{"key":"1833_CR22","doi-asserted-by":"crossref","unstructured":"Chatterjee A, Somayaji NR, Kabakis IM: Abstract WMP16: Artificial Intelligence Detection of Cerebrovascular Large Vessel Occlusion - Nine Month, 650 Patient Evaluation of the Diagnostic Accuracy and Performance of the Viz.ai LVO Algorithm. Stroke 2019, 50(Suppl_1):AWMP16-AWMP16.","DOI":"10.1161\/str.50.suppl_1.WMP16"},{"issue":"2","key":"1833_CR23","doi-asserted-by":"publisher","first-page":"156","DOI":"10.1136\/neurintsurg-2019-015135","volume":"12","author":"NM Murray","year":"2020","unstructured":"Murray NM, Unberath M, Hager GD, Hui FK: Artificial intelligence to diagnose ischemic stroke and identify large vessel occlusions: a systematic review. Journal of NeuroInterventional Surgery 2020, 12(2):156-164.","journal-title":"Journal of NeuroInterventional Surgery"},{"issue":"4","key":"1833_CR24","doi-asserted-by":"publisher","first-page":"290","DOI":"10.1038\/nbt0418-290","volume":"36","author":"FDA approves stroke-detecting AI so","year":"2018","unstructured":"FDA approves stroke-detecting AI software. Nature Biotechnology 2018, 36(4):290-290.","journal-title":"Nature Biotechnology"},{"issue":"5","key":"1833_CR25","doi-asserted-by":"publisher","first-page":"615","DOI":"10.1177\/1591019920953055","volume":"26","author":"AE Hassan","year":"2020","unstructured":"Hassan AE, Ringheanu VM, Rabah RR, Preston L, Tekle WG, Qureshi AI: Early experience utilizing artificial intelligence shows significant reduction in transfer times and length of stay in a hub and spoke model. Interventional Neuroradiology 2020, 26(5):615-622.","journal-title":"Interventional Neuroradiology"},{"key":"1833_CR26","unstructured":"Davis MA, Rao B, Cedeno P, Saha A, Zohrabian VM: Machine Learning and Improved Quality Metrics in Acute Intracranial Hemorrhage by Non-Contrast Computed Tomography. Current Problems in Diagnostic Radiology 2020."}],"container-title":["Journal of Medical Systems"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s10916-022-01833-z.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s10916-022-01833-z\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s10916-022-01833-z.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,6,21]],"date-time":"2022-06-21T03:32:43Z","timestamp":1655782363000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s10916-022-01833-z"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,6,8]]},"references-count":26,"journal-issue":{"issue":"7","published-print":{"date-parts":[[2022,7]]}},"alternative-id":["1833"],"URL":"https:\/\/doi.org\/10.1007\/s10916-022-01833-z","relation":{},"ISSN":["1573-689X"],"issn-type":[{"type":"electronic","value":"1573-689X"}],"subject":[],"published":{"date-parts":[[2022,6,8]]},"assertion":[{"value":"23 March 2022","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"16 May 2022","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"8 June 2022","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"This study approved by the Joint Institutional Review Board (KSVGH20-CT10-12) of Kaohsiung Veteran General Hospital (KSVGH). All the participants had informed consent. The medical device used for the study had premarket notification by regulatory agencies (US FDA 510(k) No.: K182875 and Taiwan Food and Drug Administration (TFDA) license No.: MOHW-MD-No. 006649).","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Ethics approval and consent to participate"}},{"value":"The authors declare no conflict of interest.","order":3,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflicts of interest"}}],"article-number":"49"}}