{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,5]],"date-time":"2026-03-05T16:04:18Z","timestamp":1772726658055,"version":"3.50.1"},"reference-count":31,"publisher":"Wiley","license":[{"start":{"date-parts":[[2022,3,21]],"date-time":"2022-03-21T00:00:00Z","timestamp":1647820800000},"content-version":"unspecified","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Jilin High-Tech Industry Development Project","award":["2016c056"],"award-info":[{"award-number":["2016c056"]}]},{"name":"Jilin High-Tech Industry Development Project","award":["201830823"],"award-info":[{"award-number":["201830823"]}]},{"name":"Jilin Science and Technology Innovation and Development Plan Project","award":["2016c056"],"award-info":[{"award-number":["2016c056"]}]},{"name":"Jilin Science and Technology Innovation and Development Plan Project","award":["201830823"],"award-info":[{"award-number":["201830823"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Journal of Healthcare Engineering"],"published-print":{"date-parts":[[2022,3,21]]},"abstract":"<jats:p>Intracranial hemorrhage (ICH) becomes a crucial healthcare emergency, which requires earlier detection and accurate assessment. Owing to the increased death rate (around 40%), the earlier recognition and classification of disease using computed tomography (CT) images are necessary to ensure a favourable prediction and restrain the existence of neurologic deficits. Since the manual diagnosis approach is time-consuming, automated ICH detection and classification models using artificial intelligence (AI) models are required. With this motivation, this study introduces an AI-enabled medical analysis tool for ICH detection and classification (AIMA-ICHDC) using CT images. The proposed AIMA-ICHDC technique aims at identifying the presence of ICH and identifying the different grades. In addition, the AIMA-ICHDC technique involves the design of glowworm swarm optimization with fuzzy entropy clustering (GSO-FEC) technique for the segmentation process. Besides, the VGG-19 model was executed for generating a collection of feature vectors and the optimal mixed-kernel-based extreme learning machine (OMKELM) model is utilized as a classifier. To optimally select the weight parameter of the MKELM technique, the coyote optimization algorithm (COA) was utilized. A wide range of simulation analyses are carried out under varying aspects. As part of the AIMA-ICHDC method, ICH can be detected and graded using a single sample. For segmentation, the AIMA-ICHDC technique uses the GSO-FEC method, which is the design of glowworm swarm optimization (GSO). The comparative outcomes highlighted the betterment of the AIMA-ICHDC technique compared to the recent state-of-the-art ICH classification approaches in terms of several measures.<\/jats:p>","DOI":"10.1155\/2022\/2017223","type":"journal-article","created":{"date-parts":[[2022,3,22]],"date-time":"2022-03-22T00:05:58Z","timestamp":1647907558000},"page":"1-13","source":"Crossref","is-referenced-by-count":17,"title":["Artificial Intelligence-Enabled Medical Analysis for Intracranial Cerebral Hemorrhage Detection and Classification"],"prefix":"10.1155","volume":"2022","author":[{"given":"Fanhua","family":"Meng","sequence":"first","affiliation":[{"name":"Stroke Unit, The Affiliated Hospital of Beihua University, Jilin 132011, Jilin, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jianhui","family":"Wang","sequence":"additional","affiliation":[{"name":"Neuromedical Center, South China Hospital Affiliated to Shenzhen University, Shenzhen 518111, Guangdong, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Hongtao","family":"Zhang","sequence":"additional","affiliation":[{"name":"Medical Imaging Center, The Affiliated Hospital of Beihua University, Jilin 132011, Jilin, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5950-3919","authenticated-orcid":true,"given":"Wei","family":"Li","sequence":"additional","affiliation":[{"name":"Stroke Unit, The Affiliated Hospital of Beihua University, Jilin 132011, Jilin, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"311","reference":[{"key":"1","doi-asserted-by":"publisher","DOI":"10.1109\/EMBC.2018.8512336"},{"key":"2","doi-asserted-by":"publisher","DOI":"10.1136\/bmj.291.6510.1675"},{"key":"3","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pone.0152351"},{"key":"4","doi-asserted-by":"publisher","DOI":"10.1038\/s41551-018-0324-9"},{"key":"5","doi-asserted-by":"publisher","DOI":"10.1148\/radiol.10092373"},{"key":"6","doi-asserted-by":"publisher","DOI":"10.1001\/jama.292.15.1823"},{"key":"7","doi-asserted-by":"publisher","DOI":"10.1089\/neu.2016.4869"},{"key":"8","doi-asserted-by":"publisher","DOI":"10.1227\/neu.0b013e3182191451"},{"key":"9","doi-asserted-by":"publisher","DOI":"10.1136\/bmj.l4225"},{"key":"10","doi-asserted-by":"publisher","DOI":"10.1007\/s00330-020-06966-8"},{"key":"11","doi-asserted-by":"publisher","DOI":"10.3390\/jcm8050683"},{"key":"12","doi-asserted-by":"publisher","DOI":"10.1117\/12.2293725"},{"key":"13","doi-asserted-by":"publisher","DOI":"10.1038\/s41467-020-19527-w"},{"key":"14","doi-asserted-by":"publisher","DOI":"10.1002\/mp.14558"},{"key":"15","doi-asserted-by":"publisher","DOI":"10.3390\/diagnostics11081449"},{"key":"16","doi-asserted-by":"publisher","DOI":"10.1007\/978-981-33-4370-2_20"},{"key":"17","doi-asserted-by":"publisher","DOI":"10.1515\/med-2020-0131"},{"key":"18","doi-asserted-by":"publisher","DOI":"10.1109\/FUZZY.2000.839049"},{"key":"19","doi-asserted-by":"publisher","DOI":"10.1016\/j.asoc.2018.01.003"},{"key":"20","doi-asserted-by":"publisher","DOI":"10.1007\/s12539-021-00467-y"},{"key":"21","doi-asserted-by":"publisher","DOI":"10.1177\/1063293X211031485"},{"key":"22","doi-asserted-by":"publisher","DOI":"10.32604\/iasc.2022.019117"},{"key":"23","unstructured":"WangL. 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