{"id":"https://openalex.org/W3206233222","doi":"https://doi.org/10.1109/cibcb49929.2021.9562848","title":"A deep learning model to predict traumatic brain injury severity and outcome from MR images","display_name":"A deep learning model to predict traumatic brain injury severity and outcome from MR images","publication_year":2021,"publication_date":"2021-10-13","ids":{"openalex":"https://openalex.org/W3206233222","doi":"https://doi.org/10.1109/cibcb49929.2021.9562848","mag":"3206233222"},"language":"en","primary_location":{"id":"doi:10.1109/cibcb49929.2021.9562848","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cibcb49929.2021.9562848","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE Conference on Computational Intelligence in Bioinformatics and Computational Biology (CIBCB)","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/A5032142798","display_name":"Dacosta Yeboah","orcid":null},"institutions":[{"id":"https://openalex.org/I119942284","display_name":"Missouri State University","ror":"https://ror.org/01d2sez20","country_code":"US","type":"education","lineage":["https://openalex.org/I119942284"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Dacosta Yeboah","raw_affiliation_strings":["Computer Science Dept., Missouri State University, Springfield, MO, USA"],"affiliations":[{"raw_affiliation_string":"Computer Science Dept., Missouri State University, Springfield, MO, USA","institution_ids":["https://openalex.org/I119942284"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5012567085","display_name":"Hung Tuan Nguyen","orcid":"https://orcid.org/0000-0003-4751-1302"},"institutions":[{"id":"https://openalex.org/I119942284","display_name":"Missouri State University","ror":"https://ror.org/01d2sez20","country_code":"US","type":"education","lineage":["https://openalex.org/I119942284"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Hung Nguyen","raw_affiliation_strings":["Computer Science Dept., Missouri State University, Springfield, MO, USA"],"affiliations":[{"raw_affiliation_string":"Computer Science Dept., Missouri State University, Springfield, MO, USA","institution_ids":["https://openalex.org/I119942284"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5046843425","display_name":"Daniel B. Hier","orcid":"https://orcid.org/0000-0002-6179-0793"},"institutions":[{"id":"https://openalex.org/I20382870","display_name":"Missouri University of Science and Technology","ror":"https://ror.org/00scwqd12","country_code":"US","type":"education","lineage":["https://openalex.org/I20382870"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Daniel B. Hier","raw_affiliation_strings":["Electrical & Computer Eng. Dept., Missouri University of Science & Technology, Rolla, MO, USA"],"affiliations":[{"raw_affiliation_string":"Electrical & Computer Eng. Dept., Missouri University of Science & Technology, Rolla, MO, USA","institution_ids":["https://openalex.org/I20382870"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5087578556","display_name":"Gayla R. Olbricht","orcid":"https://orcid.org/0000-0002-1213-2241"},"institutions":[{"id":"https://openalex.org/I20382870","display_name":"Missouri University of Science and Technology","ror":"https://ror.org/00scwqd12","country_code":"US","type":"education","lineage":["https://openalex.org/I20382870"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Gayla R. Olbricht","raw_affiliation_strings":["Mathematics and Statistics Dept., Missouri University of Science & Technology, Rolla, MO, USA"],"affiliations":[{"raw_affiliation_string":"Mathematics and Statistics Dept., Missouri University of Science & Technology, Rolla, MO, USA","institution_ids":["https://openalex.org/I20382870"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5040578359","display_name":"Tayo Obafemi-Ajayi","orcid":"https://orcid.org/0000-0002-0155-9733"},"institutions":[{"id":"https://openalex.org/I119942284","display_name":"Missouri State University","ror":"https://ror.org/01d2sez20","country_code":"US","type":"education","lineage":["https://openalex.org/I119942284"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Tayo Obafemi-Ajayi","raw_affiliation_strings":["Engineering Program Missouri State University, Springfield, MO, USA"],"affiliations":[{"raw_affiliation_string":"Engineering Program Missouri State University, Springfield, MO, USA","institution_ids":["https://openalex.org/I119942284"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5032142798"],"corresponding_institution_ids":["https://openalex.org/I119942284"],"apc_list":null,"apc_paid":null,"fwci":0.2987,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.60035898,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10416","display_name":"Traumatic Brain Injury Research","score":0.9919000267982483,"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"}},"topics":[{"id":"https://openalex.org/T10416","display_name":"Traumatic Brain Injury Research","score":0.9919000267982483,"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/T10706","display_name":"Traumatic Brain Injury and Neurovascular Disturbances","score":0.9909999966621399,"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/T12296","display_name":"Autopsy Techniques and Outcomes","score":0.988099992275238,"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/neuroimaging","display_name":"Neuroimaging","score":0.7683611512184143},{"id":"https://openalex.org/keywords/traumatic-brain-injury","display_name":"Traumatic brain injury","score":0.7355796694755554},{"id":"https://openalex.org/keywords/magnetic-resonance-imaging","display_name":"Magnetic resonance imaging","score":0.7078478336334229},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.43599486351013184},{"id":"https://openalex.org/keywords/psychology","display_name":"Psychology","score":0.4237975478172302},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.42328155040740967},{"id":"https://openalex.org/keywords/cognition","display_name":"Cognition","score":0.4132785201072693},{"id":"https://openalex.org/keywords/medicine","display_name":"Medicine","score":0.40305253863334656},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.39315199851989746},{"id":"https://openalex.org/keywords/physical-medicine-and-rehabilitation","display_name":"Physical medicine and rehabilitation","score":0.38890132308006287},{"id":"https://openalex.org/keywords/radiology","display_name":"Radiology","score":0.30457448959350586},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.22903436422348022},{"id":"https://openalex.org/keywords/neuroscience","display_name":"Neuroscience","score":0.18706554174423218},{"id":"https://openalex.org/keywords/psychiatry","display_name":"Psychiatry","score":0.14043840765953064}],"concepts":[{"id":"https://openalex.org/C58693492","wikidata":"https://www.wikidata.org/wiki/Q551875","display_name":"Neuroimaging","level":2,"score":0.7683611512184143},{"id":"https://openalex.org/C2781017439","wikidata":"https://www.wikidata.org/wiki/Q1995526","display_name":"Traumatic brain injury","level":2,"score":0.7355796694755554},{"id":"https://openalex.org/C143409427","wikidata":"https://www.wikidata.org/wiki/Q161238","display_name":"Magnetic resonance imaging","level":2,"score":0.7078478336334229},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.43599486351013184},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.4237975478172302},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.42328155040740967},{"id":"https://openalex.org/C169900460","wikidata":"https://www.wikidata.org/wiki/Q2200417","display_name":"Cognition","level":2,"score":0.4132785201072693},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.40305253863334656},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.39315199851989746},{"id":"https://openalex.org/C99508421","wikidata":"https://www.wikidata.org/wiki/Q2678675","display_name":"Physical medicine and rehabilitation","level":1,"score":0.38890132308006287},{"id":"https://openalex.org/C126838900","wikidata":"https://www.wikidata.org/wiki/Q77604","display_name":"Radiology","level":1,"score":0.30457448959350586},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.22903436422348022},{"id":"https://openalex.org/C169760540","wikidata":"https://www.wikidata.org/wiki/Q207011","display_name":"Neuroscience","level":1,"score":0.18706554174423218},{"id":"https://openalex.org/C118552586","wikidata":"https://www.wikidata.org/wiki/Q7867","display_name":"Psychiatry","level":1,"score":0.14043840765953064}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/cibcb49929.2021.9562848","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cibcb49929.2021.9562848","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE Conference on Computational Intelligence in Bioinformatics and Computational Biology (CIBCB)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":33,"referenced_works":["https://openalex.org/W30521656","https://openalex.org/W1934249711","https://openalex.org/W1966439088","https://openalex.org/W1996760171","https://openalex.org/W2042417788","https://openalex.org/W2078848335","https://openalex.org/W2080875271","https://openalex.org/W2108598243","https://openalex.org/W2163605009","https://openalex.org/W2173245751","https://openalex.org/W2194775991","https://openalex.org/W2203963179","https://openalex.org/W2204442912","https://openalex.org/W2271840356","https://openalex.org/W2484189903","https://openalex.org/W2500528961","https://openalex.org/W2621028221","https://openalex.org/W2789827414","https://openalex.org/W2890521572","https://openalex.org/W2900954917","https://openalex.org/W2902044457","https://openalex.org/W2990366895","https://openalex.org/W2997873617","https://openalex.org/W3004868960","https://openalex.org/W3025729836","https://openalex.org/W3035328251","https://openalex.org/W3082794436","https://openalex.org/W3090516356","https://openalex.org/W3105282616","https://openalex.org/W3127748371","https://openalex.org/W4255421341","https://openalex.org/W4298169162","https://openalex.org/W6684191040"],"related_works":["https://openalex.org/W4321369474","https://openalex.org/W4312417841","https://openalex.org/W2731899572","https://openalex.org/W3133861977","https://openalex.org/W4200173597","https://openalex.org/W3116150086","https://openalex.org/W2999805992","https://openalex.org/W4291897433","https://openalex.org/W3011074480","https://openalex.org/W3192840557"],"abstract_inverted_index":{"For":[0],"many":[1],"neurological":[2],"disorders,":[3],"including":[4],"traumatic":[5],"brain":[6,51],"injury":[7],"(TBI),":[8],"neuroimaging":[9],"information":[10,155],"plays":[11],"a":[12,21,39,77,83,99],"crucial":[13],"role":[14],"determining":[15],"diagnosis":[16],"and":[17,31,53,102,126],"prognosis.":[18],"TBI":[19,91,114,122],"is":[20,38],"heterogeneous":[22],"disorder":[23],"that":[24,42,89,144],"can":[25],"result":[26],"in":[27,65,162,173],"lasting":[28],"physical,":[29],"emotional":[30],"cognitive":[32],"impairments.":[33],"Magnetic":[34],"Resonance":[35],"Imaging":[36],"(MRI)":[37],"non-invasive":[40],"technique":[41],"uses":[43],"radio":[44],"waves":[45],"to":[46,151],"reveal":[47],"fine":[48],"details":[49],"of":[50,68,108,113,131,176],"anatomy":[52],"pathology.":[54],"Although":[55],"MRIs":[56],"are":[57,62],"interpreted":[58],"by":[59,137],"radiologists,":[60],"advances":[61],"being":[63],"made":[64],"the":[66,105,138,145,157,163,174],"use":[67],"deep":[69,78],"learning":[70,79,85,169],"for":[71],"MRI":[72],"interpretation.":[73],"This":[74],"work":[75],"evaluates":[76],"model":[80,97,139,170],"based":[81],"on":[82,104,121],"residual":[84,168],"convolutional":[86],"neural":[87,146],"network":[88,147],"predicts":[90],"severity":[92],"from":[93,156,179],"MR":[94,158,177],"images.":[95],"The":[96,167],"achieved":[98],"high":[100],"sensitivity":[101],"specificity":[103],"test":[106],"sample":[107],"subjects":[109,123,134,141,180],"with":[110,140,181],"varying":[111],"levels":[112],"severity.":[115],"Six":[116],"outcome":[117],"measures":[118],"were":[119],"available":[120],"at":[124],"6":[125],"12":[127],"months.":[128],"Group":[129],"comparisons":[130],"outcomes":[132],"between":[133],"correctly":[135],"classified":[136],"misclassified":[142],"suggested":[143],"may":[148],"be":[149],"able":[150],"identify":[152],"latent":[153],"predictive":[154],"images":[159,178],"not":[160],"incorporated":[161],"ground":[164],"truth":[165],"labels.":[166],"shows":[171],"promise":[172],"classification":[175],"TBI.":[182]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":1}],"updated_date":"2025-11-25T21:42:39.735039","created_date":"2025-10-10T00:00:00"}
