{"id":"https://openalex.org/W2588863357","doi":"https://doi.org/10.1109/iww-bci.2017.7858167","title":"Classification of computed tomography scanner manufacturer using support vector machine","display_name":"Classification of computed tomography scanner manufacturer using support vector machine","publication_year":2017,"publication_date":"2017-01-01","ids":{"openalex":"https://openalex.org/W2588863357","doi":"https://doi.org/10.1109/iww-bci.2017.7858167","mag":"2588863357"},"language":"en","primary_location":{"id":"doi:10.1109/iww-bci.2017.7858167","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iww-bci.2017.7858167","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 5th International Winter Conference on Brain-Computer Interface (BCI)","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5060632929","display_name":"Seung-Bo Lee","orcid":"https://orcid.org/0000-0002-6817-5793"},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Seung-Bo Lee","raw_affiliation_strings":["Dept. of brain and cognitive engineering, Clinical Neuro Modeling Lab., Seoul, Korea"],"affiliations":[{"raw_affiliation_string":"Dept. of brain and cognitive engineering, Clinical Neuro Modeling Lab., Seoul, Korea","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5011130828","display_name":"Eun\u2010Jin Jeong","orcid":"https://orcid.org/0000-0001-6870-9372"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Eun-Jin Jeong","raw_affiliation_strings":["Dept. of brain and cognitive engineering, Clinical Neuro Modeling Lab., Seoul, Korea"],"affiliations":[{"raw_affiliation_string":"Dept. of brain and cognitive engineering, Clinical Neuro Modeling Lab., Seoul, Korea","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5043417988","display_name":"Yunsik Son","orcid":"https://orcid.org/0000-0002-2580-4393"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yunsik Son","raw_affiliation_strings":["Dept. of brain and cognitive engineering, Clinical Neuro Modeling Lab., Seoul, Korea"],"affiliations":[{"raw_affiliation_string":"Dept. of brain and cognitive engineering, Clinical Neuro Modeling Lab., Seoul, Korea","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101947623","display_name":"Dong\u2010Joo Kim","orcid":"https://orcid.org/0000-0002-0988-2236"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Dong-Joo Kim","raw_affiliation_strings":["Dept. of brain and cognitive engineering, Clinical Neuro Modeling Lab., Seoul, Korea"],"affiliations":[{"raw_affiliation_string":"Dept. of brain and cognitive engineering, Clinical Neuro Modeling Lab., Seoul, Korea","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5060632929"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.5072,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.65773885,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":"2","issue":null,"first_page":"85","last_page":"87"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10706","display_name":"Traumatic Brain Injury and Neurovascular Disturbances","score":0.9994999766349792,"subfield":{"id":"https://openalex.org/subfields/2728","display_name":"Neurology"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},"topics":[{"id":"https://openalex.org/T10706","display_name":"Traumatic Brain Injury and Neurovascular Disturbances","score":0.9994999766349792,"subfield":{"id":"https://openalex.org/subfields/2728","display_name":"Neurology"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},{"id":"https://openalex.org/T10227","display_name":"Acute Ischemic Stroke Management","score":0.9843000173568726,"subfield":{"id":"https://openalex.org/subfields/2713","display_name":"Epidemiology"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},{"id":"https://openalex.org/T10844","display_name":"Radiation Dose and Imaging","score":0.978600025177002,"subfield":{"id":"https://openalex.org/subfields/2741","display_name":"Radiology, Nuclear Medicine and Imaging"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/scanner","display_name":"Scanner","score":0.8481738567352295},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.7387806177139282},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5806692838668823},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5663272738456726},{"id":"https://openalex.org/keywords/hyperparameter","display_name":"Hyperparameter","score":0.5620793104171753},{"id":"https://openalex.org/keywords/gaussian-function","display_name":"Gaussian function","score":0.5306253433227539},{"id":"https://openalex.org/keywords/computed-tomography","display_name":"Computed tomography","score":0.5136870741844177},{"id":"https://openalex.org/keywords/cross-validation","display_name":"Cross-validation","score":0.4794679880142212},{"id":"https://openalex.org/keywords/hyperparameter-optimization","display_name":"Hyperparameter optimization","score":0.4547310769557953},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.44700926542282104},{"id":"https://openalex.org/keywords/gaussian","display_name":"Gaussian","score":0.4193432629108429},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.3652941584587097},{"id":"https://openalex.org/keywords/radiology","display_name":"Radiology","score":0.24196171760559082},{"id":"https://openalex.org/keywords/medicine","display_name":"Medicine","score":0.2124144732952118},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.09659898281097412}],"concepts":[{"id":"https://openalex.org/C2779751349","wikidata":"https://www.wikidata.org/wiki/Q1474480","display_name":"Scanner","level":2,"score":0.8481738567352295},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.7387806177139282},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5806692838668823},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5663272738456726},{"id":"https://openalex.org/C8642999","wikidata":"https://www.wikidata.org/wiki/Q4171168","display_name":"Hyperparameter","level":2,"score":0.5620793104171753},{"id":"https://openalex.org/C7218915","wikidata":"https://www.wikidata.org/wiki/Q1054475","display_name":"Gaussian function","level":3,"score":0.5306253433227539},{"id":"https://openalex.org/C544519230","wikidata":"https://www.wikidata.org/wiki/Q32566","display_name":"Computed tomography","level":2,"score":0.5136870741844177},{"id":"https://openalex.org/C27181475","wikidata":"https://www.wikidata.org/wiki/Q541014","display_name":"Cross-validation","level":2,"score":0.4794679880142212},{"id":"https://openalex.org/C10485038","wikidata":"https://www.wikidata.org/wiki/Q48996162","display_name":"Hyperparameter optimization","level":3,"score":0.4547310769557953},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.44700926542282104},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.4193432629108429},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3652941584587097},{"id":"https://openalex.org/C126838900","wikidata":"https://www.wikidata.org/wiki/Q77604","display_name":"Radiology","level":1,"score":0.24196171760559082},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.2124144732952118},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.09659898281097412},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/iww-bci.2017.7858167","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iww-bci.2017.7858167","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 5th International Winter Conference on Brain-Computer Interface (BCI)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Good health and well-being","score":0.6700000166893005,"id":"https://metadata.un.org/sdg/3"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":14,"referenced_works":["https://openalex.org/W175058090","https://openalex.org/W192658229","https://openalex.org/W1976928781","https://openalex.org/W1994195447","https://openalex.org/W1996760171","https://openalex.org/W2094739585","https://openalex.org/W2103831776","https://openalex.org/W2127646612","https://openalex.org/W2143611051","https://openalex.org/W2149250475","https://openalex.org/W2187183197","https://openalex.org/W2282078507","https://openalex.org/W6607830178","https://openalex.org/W6686822178"],"related_works":["https://openalex.org/W2953665647","https://openalex.org/W4281646320","https://openalex.org/W4205712847","https://openalex.org/W3169687406","https://openalex.org/W2954882791","https://openalex.org/W4287818966","https://openalex.org/W4388119537","https://openalex.org/W3014750173","https://openalex.org/W3114025147","https://openalex.org/W3192751261"],"abstract_inverted_index":{"Computed":[0],"tomography":[1],"(CT)":[2],"is":[3,122],"useful":[4],"to":[5,22,180,193],"investigate":[6],"the":[7,46,60,126,131,144,147,181,188,195,199],"presence":[8],"and":[9,25,40,45,98,143,163,184],"severity":[10],"of":[11,16,43,48,62,112],"injury":[12,19],"during":[13],"acute":[14],"stage":[15],"traumatic":[17],"brain":[18,200],"(TBI)":[20],"due":[21],"its":[23],"availability":[24],"short":[26],"image":[27],"acquisition":[28],"time.":[29],"Recently,":[30],"quantitative":[31,58,94,196],"CT":[32,63,72,127,201],"analysis":[33,95,197],"have":[34],"shown":[35],"promising":[36],"results":[37,172],"in":[38,176],"objective":[39],"accurate":[41],"assessment":[42],"lesion":[44],"prediction":[47],"outcome.":[49],"To":[50],"conduct":[51,194],"further":[52],"multicenter,":[53],"longitudinal":[54],"follow-up":[55],"studies":[56],"using":[57,117],"analysis,":[59],"effect":[61],"scanner":[64,91,132,182],"manufacturer":[65,189],"should":[66,190],"be":[67,191],"investigated.":[68],"In":[69],"this":[70],"study,":[71],"images":[73,85,128],"were":[74,86,107,137],"acquired":[75,104],"from":[76],"326":[77],"subjects":[78],"without":[79],"any":[80],"apparent":[81],"intracranial":[82],"abnormalities.":[83],"The":[84,93,103,134,153,171],"scanned":[87],"by":[88,149],"three":[89],"different":[90],"manufacturers.":[92,133],"was":[96,157],"performed":[97],"plotted":[99],"as":[100,109],"density":[101,105,177],"distribution.":[102],"distributions":[106],"served":[108],"input":[110],"features":[111],"support":[113],"vector":[114],"machine":[115],"(SVM)":[116],"Gaussian":[118],"kernel":[119],"function,":[120],"which":[121],"designed":[123],"for":[124],"classifying":[125],"based":[129],"on":[130,198],"optimal":[135],"hyperparameters":[136],"explored":[138],"via":[139],"grid":[140],"search":[141],"test":[142],"model":[145],"increased":[146],"robustness":[148],"5-fold":[150],"cross":[151],"validation.":[152],"best":[154],"predictive":[155],"performance":[156],"obtained":[158],"when":[159],"C":[160],"=":[161,165,168],"100":[162],"\u03b3":[164],"0.1":[166],"(accuracy":[167],"91.1":[169],"%).":[170],"showed":[173],"significant":[174],"difference":[175],"distribution":[178],"according":[179],"manufacturers,":[183],"thus":[185],"suggest":[186],"that":[187],"standardized":[192],"images.":[202]},"counts_by_year":[{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":1},{"year":2017,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}