{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,16]],"date-time":"2026-07-16T15:46:03Z","timestamp":1784216763666,"version":"3.55.0"},"reference-count":84,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","license":[{"start":{"date-parts":[[2024,1,1]],"date-time":"2024-01-01T00:00:00Z","timestamp":1704067200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100004530","name":"Universiti Putra Malaysia through Putra Grant Scheme","doi-asserted-by":"publisher","award":["GP\/2020\/9692500"],"award-info":[{"award-number":["GP\/2020\/9692500"]}],"id":[{"id":"10.13039\/501100004530","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100003093","name":"Ministry of Higher Education Malaysia through the Fundamental Research Grant Scheme","doi-asserted-by":"publisher","award":["FRGS\/1\/2023\/ICT06\/UPM\/02\/1"],"award-info":[{"award-number":["FRGS\/1\/2023\/ICT06\/UPM\/02\/1"]}],"id":[{"id":"10.13039\/501100003093","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Access"],"published-print":{"date-parts":[[2024]]},"DOI":"10.1109\/access.2024.3373885","type":"journal-article","created":{"date-parts":[[2024,3,5]],"date-time":"2024-03-05T19:15:20Z","timestamp":1709666120000},"page":"37540-37556","source":"Crossref","is-referenced-by-count":19,"title":["Road Crash Injury Severity Prediction Using a Graph Neural Network Framework"],"prefix":"10.1109","volume":"12","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-4170-5360","authenticated-orcid":false,"given":"Karim A.","family":"Sattar","sequence":"first","affiliation":[{"name":"Department of Computer Science, Faculty of Computer Science and Information Technology, Universiti Putra Malaysia (UPM), Serdang, Malaysia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8874-1417","authenticated-orcid":false,"given":"Iskandar","family":"Ishak","sequence":"additional","affiliation":[{"name":"Department of Computer Science, Faculty of Computer Science and Information Technology, Universiti Putra Malaysia (UPM), Serdang, Malaysia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7947-8792","authenticated-orcid":false,"given":"Lilly Suriani","family":"Affendey","sequence":"additional","affiliation":[{"name":"Department of Computer Science, Faculty of Computer Science and Information Technology, Universiti Putra Malaysia (UPM), Serdang, Malaysia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7818-8208","authenticated-orcid":false,"given":"Siti Nurulain Binti","family":"Mohd Rum","sequence":"additional","affiliation":[{"name":"Department of Computer Science, Faculty of Computer Science and Information Technology, Universiti Putra Malaysia (UPM), Serdang, Malaysia"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"263","reference":[{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1016\/j.trip.2023.100814"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.3390\/ijerph17093155"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1016\/j.proeng.2012.08.108"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-031-12011-4_94"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1016\/j.aap.2021.106504"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1016\/j.trc.2020.102683"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1016\/j.trb.2021.09.008"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1109\/ITSC.2006.1707456"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2021.3072914"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1155\/2018\/9841498"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1177\/0361198118758684"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1016\/j.aap.2016.06.015"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1002\/atr.5670410107"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1139\/cjce-2018-0262"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1016\/j.aap.2019.105355"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.3390\/ijerph17020395"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1155\/2020\/8870497"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1109\/ICCSN.2019.8905362"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.3390\/app10010129"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.3390\/app13010233"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1038\/s41598-022-25361-5"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-10374-3_9"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.3390\/app12041790"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1109\/ICITE56321.2022.10101376"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1007\/s00521-019-04695-8"},{"key":"ref26","article-title":"An investigation of categorical variable encoding techniques in machine learning: Binary versus one-hot and feature hashing","author":"Seger","year":"2018"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.3390\/math9080830"},{"key":"ref28","first-page":"4343","article-title":"Graph construction for semi-supervised learning","volume-title":"Proc. 24th Int. Conf. Artif. Intell.","author":"Berton"},{"key":"ref29","article-title":"Revisiting k-nearest neighbor graph construction on high-dimensional data: Experiments and analyses","author":"Yingfan","year":"2021","journal-title":"arXiv:2112.02234"},{"key":"ref30","first-page":"1025","article-title":"Inductive representation learning on large graphs","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","volume":"30","author":"Hamilton"},{"key":"ref31","article-title":"TabGSL: Graph structure learning for tabular data prediction","author":"Chiehen Liao","year":"2023","journal-title":"arXiv:2305.15843"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1007\/s12652-021-03592-0"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2021.3104357"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-73197-7_23"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1016\/j.patcog.2022.108694"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.1007\/s10844-021-00693-2"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.1109\/FUZZ-IEEE55066.2022.9882620"},{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.1007\/s10489-023-04899-5"},{"key":"ref39","doi-asserted-by":"publisher","DOI":"10.1088\/2632-2153\/ac2c5d"},{"key":"ref40","doi-asserted-by":"publisher","DOI":"10.1016\/j.ymeth.2021.01.004"},{"key":"ref41","doi-asserted-by":"publisher","DOI":"10.3390\/diagnostics13121981"},{"key":"ref42","doi-asserted-by":"publisher","DOI":"10.1007\/s11063-022-10985-5"},{"key":"ref43","article-title":"Boost then convolve: Gradient boosting meets graph neural networks","author":"Ivanov","year":"2021","journal-title":"arXiv:2101.08543"},{"key":"ref44","doi-asserted-by":"publisher","DOI":"10.1080\/15389588.2018.1482537"},{"key":"ref45","doi-asserted-by":"publisher","DOI":"10.1016\/j.aap.2019.07.012"},{"key":"ref46","doi-asserted-by":"publisher","DOI":"10.1080\/19439962.2018.1551257"},{"key":"ref47","doi-asserted-by":"publisher","DOI":"10.1007\/s00500-023-08001-6"},{"key":"ref48","doi-asserted-by":"publisher","DOI":"10.1016\/j.eastsj.2021.100040"},{"key":"ref49","doi-asserted-by":"publisher","DOI":"10.3390\/app7060476"},{"key":"ref50","doi-asserted-by":"publisher","DOI":"10.1016\/j.trip.2023.100801"},{"key":"ref51","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pone.0281901"},{"key":"ref52","doi-asserted-by":"publisher","DOI":"10.1016\/j.chaos.2023.113245"},{"key":"ref53","doi-asserted-by":"publisher","DOI":"10.1080\/13588265.2022.2074643"},{"key":"ref54","doi-asserted-by":"publisher","DOI":"10.3390\/su15032014"},{"key":"ref55","doi-asserted-by":"publisher","DOI":"10.1007\/s13177-023-00351-7"},{"key":"ref56","doi-asserted-by":"publisher","DOI":"10.3233\/IDA-216398"},{"key":"ref57","doi-asserted-by":"publisher","DOI":"10.3390\/su14074101"},{"key":"ref58","volume-title":"Road Safety Data","year":"2023"},{"key":"ref59","doi-asserted-by":"publisher","DOI":"10.1023\/A:1010933404324"},{"key":"ref60","doi-asserted-by":"publisher","DOI":"10.1145\/2939672.2939785"},{"key":"ref61","doi-asserted-by":"publisher","DOI":"10.1016\/j.oceaneng.2020.107526"},{"key":"ref62","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2018.2818678"},{"key":"ref63","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-32520-6_69"},{"key":"ref64","doi-asserted-by":"publisher","DOI":"10.1007\/s42452-020-3060-1"},{"key":"ref65","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-031-01588-5"},{"key":"ref66","doi-asserted-by":"publisher","DOI":"10.1146\/annurev.soc.27.1.415"},{"key":"ref67","first-page":"321","article-title":"Learning with local and global consistency","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","volume":"16","author":"Zhou"},{"key":"ref68","article-title":"Semi-supervised classification with graph convolutional networks","author":"Kipf","year":"2016","journal-title":"arXiv:1609.02907"},{"key":"ref69","article-title":"Graph attention networks","author":"Veli\u010d kovi\u0107","year":"2017","journal-title":"arXiv:1710.10903"},{"key":"ref70","doi-asserted-by":"publisher","DOI":"10.5555\/1953048.2078195"},{"key":"ref71","doi-asserted-by":"publisher","DOI":"10.1109\/TVCG.2017.2745141"},{"key":"ref72","article-title":"Fast graph representation learning with PyTorch geometric","author":"Fey","year":"2019","journal-title":"arXiv:1903.02428"},{"key":"ref73","volume-title":"Exploring SageConv: A Powerful Graph Neural Network Architecture","author":"Sheikh","year":"2023"},{"key":"ref74","doi-asserted-by":"publisher","DOI":"10.1093\/bioinformatics\/btad774"},{"key":"ref75","doi-asserted-by":"publisher","DOI":"10.1186\/s12859-023-05251-x"},{"key":"ref76","doi-asserted-by":"publisher","DOI":"10.1016\/j.trb.2023.102783"},{"key":"ref77","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2021.3084050"},{"key":"ref78","doi-asserted-by":"publisher","DOI":"10.1186\/s12864-019-6413-7"},{"key":"ref79","doi-asserted-by":"publisher","DOI":"10.1080\/17457300.2021.1928233"},{"key":"ref80","doi-asserted-by":"publisher","DOI":"10.1109\/IRI49571.2020.00039"},{"key":"ref81","first-page":"5453","article-title":"Representation learning on graphs with jumping knowledge networks","volume-title":"Proc. Int. Conf. Mach. Learn.","author":"Xu"},{"key":"ref82","doi-asserted-by":"publisher","DOI":"10.1162\/089976698300017197"},{"key":"ref83","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2020.3002191"},{"key":"ref84","volume-title":"Data Mining: Practical Machine Learning Tools and Techniques","author":"Witten","year":"2016"}],"container-title":["IEEE Access"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/6287639\/10380310\/10460524.pdf?arnumber=10460524","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,3,26]],"date-time":"2024-03-26T12:58:47Z","timestamp":1711457927000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/10460524\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024]]},"references-count":84,"URL":"https:\/\/doi.org\/10.1109\/access.2024.3373885","relation":{},"ISSN":["2169-3536"],"issn-type":[{"value":"2169-3536","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024]]}}}