{"id":"https://openalex.org/W2553143642","doi":"https://doi.org/10.1109/ijcnn.2016.7727336","title":"A hybrid sequential feature selection approach for the diagnosis of Alzheimer's Disease","display_name":"A hybrid sequential feature selection approach for the diagnosis of Alzheimer's Disease","publication_year":2016,"publication_date":"2016-07-01","ids":{"openalex":"https://openalex.org/W2553143642","doi":"https://doi.org/10.1109/ijcnn.2016.7727336","mag":"2553143642"},"language":"en","primary_location":{"id":"doi:10.1109/ijcnn.2016.7727336","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn.2016.7727336","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 International Joint Conference on Neural Networks (IJCNN)","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/A5082137392","display_name":"Yang Han","orcid":"https://orcid.org/0000-0003-3782-4655"},"institutions":[{"id":"https://openalex.org/I116953780","display_name":"Tongji University","ror":"https://ror.org/03rc6as71","country_code":"CN","type":"education","lineage":["https://openalex.org/I116953780"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Yang Han","raw_affiliation_strings":["Department of Computer Science And Technology, Tongji University, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science And Technology, Tongji University, Shanghai, China","institution_ids":["https://openalex.org/I116953780"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101736200","display_name":"Xing-Ming Zhao","orcid":"https://orcid.org/0000-0002-3335-6439"},"institutions":[{"id":"https://openalex.org/I116953780","display_name":"Tongji University","ror":"https://ror.org/03rc6as71","country_code":"CN","type":"education","lineage":["https://openalex.org/I116953780"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xing-Ming Zhao","raw_affiliation_strings":["Department of Computer Science And Technology, Tongji University, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science And Technology, Tongji University, Shanghai, China","institution_ids":["https://openalex.org/I116953780"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5082137392"],"corresponding_institution_ids":["https://openalex.org/I116953780"],"apc_list":null,"apc_paid":null,"fwci":0.5224,"has_fulltext":false,"cited_by_count":6,"citation_normalized_percentile":{"value":0.73259235,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"1216","last_page":"1220"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12702","display_name":"Brain Tumor Detection and Classification","score":0.9919999837875366,"subfield":{"id":"https://openalex.org/subfields/2808","display_name":"Neurology"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},"topics":[{"id":"https://openalex.org/T12702","display_name":"Brain Tumor Detection and Classification","score":0.9919999837875366,"subfield":{"id":"https://openalex.org/subfields/2808","display_name":"Neurology"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T11396","display_name":"Artificial Intelligence in Healthcare","score":0.9886999726295471,"subfield":{"id":"https://openalex.org/subfields/3605","display_name":"Health Information Management"},"field":{"id":"https://openalex.org/fields/36","display_name":"Health Professions"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},{"id":"https://openalex.org/T10009","display_name":"Dementia and Cognitive Impairment Research","score":0.9836999773979187,"subfield":{"id":"https://openalex.org/subfields/2738","display_name":"Psychiatry and Mental health"},"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/feature-selection","display_name":"Feature selection","score":0.7497850656509399},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7239440083503723},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6391164064407349},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.6151612401008606},{"id":"https://openalex.org/keywords/benchmarking","display_name":"Benchmarking","score":0.5573067665100098},{"id":"https://openalex.org/keywords/positron-emission-tomography","display_name":"Positron emission tomography","score":0.5353121757507324},{"id":"https://openalex.org/keywords/selection","display_name":"Selection (genetic algorithm)","score":0.5350638031959534},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.501842737197876},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4842336177825928},{"id":"https://openalex.org/keywords/magnetic-resonance-imaging","display_name":"Magnetic resonance imaging","score":0.45228928327560425},{"id":"https://openalex.org/keywords/neuroimaging","display_name":"Neuroimaging","score":0.44535380601882935},{"id":"https://openalex.org/keywords/medicine","display_name":"Medicine","score":0.11778879165649414},{"id":"https://openalex.org/keywords/radiology","display_name":"Radiology","score":0.09405159950256348}],"concepts":[{"id":"https://openalex.org/C148483581","wikidata":"https://www.wikidata.org/wiki/Q446488","display_name":"Feature selection","level":2,"score":0.7497850656509399},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7239440083503723},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6391164064407349},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.6151612401008606},{"id":"https://openalex.org/C86251818","wikidata":"https://www.wikidata.org/wiki/Q816754","display_name":"Benchmarking","level":2,"score":0.5573067665100098},{"id":"https://openalex.org/C2775842073","wikidata":"https://www.wikidata.org/wiki/Q208376","display_name":"Positron emission tomography","level":2,"score":0.5353121757507324},{"id":"https://openalex.org/C81917197","wikidata":"https://www.wikidata.org/wiki/Q628760","display_name":"Selection (genetic algorithm)","level":2,"score":0.5350638031959534},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.501842737197876},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4842336177825928},{"id":"https://openalex.org/C143409427","wikidata":"https://www.wikidata.org/wiki/Q161238","display_name":"Magnetic resonance imaging","level":2,"score":0.45228928327560425},{"id":"https://openalex.org/C58693492","wikidata":"https://www.wikidata.org/wiki/Q551875","display_name":"Neuroimaging","level":2,"score":0.44535380601882935},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.11778879165649414},{"id":"https://openalex.org/C126838900","wikidata":"https://www.wikidata.org/wiki/Q77604","display_name":"Radiology","level":1,"score":0.09405159950256348},{"id":"https://openalex.org/C118552586","wikidata":"https://www.wikidata.org/wiki/Q7867","display_name":"Psychiatry","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C144133560","wikidata":"https://www.wikidata.org/wiki/Q4830453","display_name":"Business","level":0,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C162853370","wikidata":"https://www.wikidata.org/wiki/Q39809","display_name":"Marketing","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ijcnn.2016.7727336","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn.2016.7727336","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 International Joint Conference on Neural Networks (IJCNN)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":30,"referenced_works":["https://openalex.org/W939280201","https://openalex.org/W1589199242","https://openalex.org/W1849729440","https://openalex.org/W2019587683","https://openalex.org/W2034394250","https://openalex.org/W2044151123","https://openalex.org/W2059658584","https://openalex.org/W2065731782","https://openalex.org/W2067696780","https://openalex.org/W2087347434","https://openalex.org/W2099111195","https://openalex.org/W2112436745","https://openalex.org/W2125756390","https://openalex.org/W2128251808","https://openalex.org/W2147768282","https://openalex.org/W2151920318","https://openalex.org/W2165363188","https://openalex.org/W2472882072","https://openalex.org/W2478708596","https://openalex.org/W2800394774","https://openalex.org/W3017143921","https://openalex.org/W3140968660","https://openalex.org/W3147668634","https://openalex.org/W4249565903","https://openalex.org/W4321613415","https://openalex.org/W6638875480","https://openalex.org/W6674851815","https://openalex.org/W6678621587","https://openalex.org/W6776565550","https://openalex.org/W7048060829"],"related_works":["https://openalex.org/W4238897586","https://openalex.org/W435179959","https://openalex.org/W2619091065","https://openalex.org/W2059640416","https://openalex.org/W1490753184","https://openalex.org/W2284465472","https://openalex.org/W2291782699","https://openalex.org/W1993948687","https://openalex.org/W4386564352","https://openalex.org/W2952668426"],"abstract_inverted_index":{"The":[0,141],"timely":[1],"and":[2,30,53,87,127],"accurate":[3,61],"diagnosis":[4,41,85,124],"of":[5,15,22,42,116,125,136,157],"Alzheimer's":[6],"Disease":[7],"(AD)":[8],"is":[9,153],"important":[10],"for":[11,39],"preventing":[12],"the":[13,16,40,47,75,84,89,95,113,117,134,145],"progress":[14],"irreversible":[17],"disease.":[18],"Recently,":[19],"various":[20],"types":[21],"imaging":[23],"techniques,":[24],"e.g.":[25],"Magnetic":[26],"Resonance":[27],"Imaging":[28],"(MRI)":[29],"Positron":[31],"Emission":[32],"Tomography":[33],"(PET),":[34],"have":[35],"been":[36],"widely":[37],"used":[38],"AD.":[43],"Despite":[44],"their":[45],"usefulness,":[46],"image":[48],"data":[49,147],"generated":[50],"are":[51],"high-dimensional":[52],"noisy":[54],"which":[55,81],"make":[56],"it":[57],"difficult":[58],"to":[59,73],"give":[60],"diagnosis.":[62],"In":[63],"this":[64],"paper,":[65],"we":[66],"propose":[67],"a":[68],"novel":[69],"feature":[70,107],"selection":[71,108],"approach":[72,103,120,152],"detect":[74],"informative":[76],"features":[77],"from":[78],"MRI":[79],"data,":[80],"improves":[82],"both":[83],"accuracy":[86],"reduces":[88],"computational":[90],"cost.":[91],"Benchmarking":[92],"results":[93],"on":[94,144],"AD":[96,126],"challenge":[97],"datasets":[98],"show":[99],"that":[100,149],"our":[101,119,150],"proposed":[102,151],"outperforms":[104],"other":[105],"popular":[106],"methods.":[109],"Furthermore,":[110],"compared":[111],"with":[112,131],"top":[114],"winners":[115],"challenge,":[118],"performs":[121],"best":[122],"in":[123,133,155],"has":[128],"comparable":[129],"performance":[130,143],"others":[132],"detection":[135],"mild":[137],"cognitive":[138],"impairments":[139],"(MCIs).":[140],"good":[142],"real":[146],"demonstrate":[148],"effective":[154],"prediction":[156],"ADs.":[158]},"counts_by_year":[{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":1},{"year":2019,"cited_by_count":1},{"year":2017,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}