{"id":"https://openalex.org/W4415912994","doi":"https://doi.org/10.1109/ccwc62904.2025.10903702","title":"GA-SFS: A Two-Stage Hybrid Algorithm for Feature Selection in Biomedical Data","display_name":"GA-SFS: A Two-Stage Hybrid Algorithm for Feature Selection in Biomedical Data","publication_year":2025,"publication_date":"2025-01-06","ids":{"openalex":"https://openalex.org/W4415912994","doi":"https://doi.org/10.1109/ccwc62904.2025.10903702"},"language":"en","primary_location":{"id":"doi:10.1109/ccwc62904.2025.10903702","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ccwc62904.2025.10903702","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE 15th Annual Computing and Communication Workshop and Conference (CCWC)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5002106116","display_name":"Brian Bales","orcid":null},"institutions":[{"id":"https://openalex.org/I157638225","display_name":"California State University, Northridge","ror":"https://ror.org/005f5hv41","country_code":"US","type":"education","lineage":["https://openalex.org/I157638225"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Brian Bales","raw_affiliation_strings":["California State University, Northridge,Department of Computer Science,California,USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"California State University, Northridge,Department of Computer Science,California,USA","institution_ids":["https://openalex.org/I157638225"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5119394221","display_name":"Monitha Davuluri","orcid":null},"institutions":[{"id":"https://openalex.org/I157638225","display_name":"California State University, Northridge","ror":"https://ror.org/005f5hv41","country_code":"US","type":"education","lineage":["https://openalex.org/I157638225"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Monitha Davuluri","raw_affiliation_strings":["California State University, Northridge,Department of Computer Science,California,USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"California State University, Northridge,Department of Computer Science,California,USA","institution_ids":["https://openalex.org/I157638225"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5091820414","display_name":"Rashida Hasan","orcid":"https://orcid.org/0000-0002-6231-8116"},"institutions":[{"id":"https://openalex.org/I157638225","display_name":"California State University, Northridge","ror":"https://ror.org/005f5hv41","country_code":"US","type":"education","lineage":["https://openalex.org/I157638225"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Rashida Hasan","raw_affiliation_strings":["California State University, Northridge,Department of Computer Science,California,USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"California State University, Northridge,Department of Computer Science,California,USA","institution_ids":["https://openalex.org/I157638225"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I157638225"],"apc_list":null,"apc_paid":null,"fwci":5.6776,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.95006658,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":91,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"00421","last_page":"00426"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10885","display_name":"Gene expression and cancer classification","score":0.18639999628067017,"subfield":{"id":"https://openalex.org/subfields/1312","display_name":"Molecular Biology"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},"topics":[{"id":"https://openalex.org/T10885","display_name":"Gene expression and cancer classification","score":0.18639999628067017,"subfield":{"id":"https://openalex.org/subfields/1312","display_name":"Molecular Biology"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T10057","display_name":"Face and Expression Recognition","score":0.18279999494552612,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T12535","display_name":"Machine Learning and Data Classification","score":0.1597999930381775,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/feature-selection","display_name":"Feature selection","score":0.7806000113487244},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.5999000072479248},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.4643999934196472},{"id":"https://openalex.org/keywords/selection","display_name":"Selection (genetic algorithm)","score":0.43380001187324524},{"id":"https://openalex.org/keywords/genetic-algorithm","display_name":"Genetic algorithm","score":0.4318000078201294},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4165000021457672},{"id":"https://openalex.org/keywords/noisy-data","display_name":"Noisy data","score":0.3668000102043152},{"id":"https://openalex.org/keywords/hybrid-algorithm","display_name":"Hybrid algorithm (constraint satisfaction)","score":0.32359999418258667}],"concepts":[{"id":"https://openalex.org/C148483581","wikidata":"https://www.wikidata.org/wiki/Q446488","display_name":"Feature selection","level":2,"score":0.7806000113487244},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7369999885559082},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.602400004863739},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.5999000072479248},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.5659000277519226},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4884999990463257},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.4643999934196472},{"id":"https://openalex.org/C81917197","wikidata":"https://www.wikidata.org/wiki/Q628760","display_name":"Selection (genetic algorithm)","level":2,"score":0.43380001187324524},{"id":"https://openalex.org/C8880873","wikidata":"https://www.wikidata.org/wiki/Q187787","display_name":"Genetic algorithm","level":2,"score":0.4318000078201294},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4165000021457672},{"id":"https://openalex.org/C2781170535","wikidata":"https://www.wikidata.org/wiki/Q30587856","display_name":"Noisy data","level":2,"score":0.3668000102043152},{"id":"https://openalex.org/C62469222","wikidata":"https://www.wikidata.org/wiki/Q17092103","display_name":"Hybrid algorithm (constraint satisfaction)","level":5,"score":0.32359999418258667},{"id":"https://openalex.org/C16811321","wikidata":"https://www.wikidata.org/wiki/Q17138905","display_name":"Minimum redundancy feature selection","level":3,"score":0.3059000074863434},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.3028999865055084},{"id":"https://openalex.org/C93959086","wikidata":"https://www.wikidata.org/wiki/Q6888345","display_name":"Model selection","level":2,"score":0.2913999855518341},{"id":"https://openalex.org/C110083411","wikidata":"https://www.wikidata.org/wiki/Q1744628","display_name":"Statistical classification","level":2,"score":0.289000004529953},{"id":"https://openalex.org/C201797286","wikidata":"https://www.wikidata.org/wiki/Q4914986","display_name":"Biological data","level":2,"score":0.27900001406669617},{"id":"https://openalex.org/C50897621","wikidata":"https://www.wikidata.org/wiki/Q2665508","display_name":"Hybrid system","level":2,"score":0.27320000529289246},{"id":"https://openalex.org/C2984324147","wikidata":"https://www.wikidata.org/wiki/Q3080021","display_name":"Gene selection","level":5,"score":0.27160000801086426},{"id":"https://openalex.org/C198531522","wikidata":"https://www.wikidata.org/wiki/Q485146","display_name":"Sample (material)","level":2,"score":0.2639000117778778},{"id":"https://openalex.org/C3018263672","wikidata":"https://www.wikidata.org/wiki/Q1296251","display_name":"Efficient algorithm","level":2,"score":0.2538999915122986}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ccwc62904.2025.10903702","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ccwc62904.2025.10903702","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE 15th Annual Computing and Communication Workshop and Conference (CCWC)","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":17,"referenced_works":["https://openalex.org/W2015668472","https://openalex.org/W2019583087","https://openalex.org/W2964278775","https://openalex.org/W2979665139","https://openalex.org/W3136399649","https://openalex.org/W3154248386","https://openalex.org/W3154955351","https://openalex.org/W3186962463","https://openalex.org/W3208477548","https://openalex.org/W3216978859","https://openalex.org/W4206558648","https://openalex.org/W4220853618","https://openalex.org/W4224290700","https://openalex.org/W4289236186","https://openalex.org/W4388487338","https://openalex.org/W4392714002","https://openalex.org/W4392946440"],"related_works":[],"abstract_inverted_index":{"In":[0],"biomedical":[1,82],"data":[2,35],"analysis,":[3],"feature":[4,95],"selection":[5,96],"is":[6],"crucial,":[7],"particularly":[8],"for":[9],"high-dimensional":[10],"datasets":[11,22,83,89],"where":[12],"redundant":[13],"or":[14,44],"irrelevant":[15],"features":[16,79],"might":[17],"affect":[18],"model":[19,50],"performance.":[20],"Biomedical":[21],"introduce":[23],"additional":[24],"challenges,":[25],"such":[26],"as":[27],"high":[28],"dimensionality,":[29],"small":[30],"sample":[31],"sizes,":[32],"and":[33,52],"complex":[34,81],"structures.":[36],"Addressing":[37],"these":[38,56],"issues":[39],"often":[40],"requires":[41],"hybrid,":[42],"adaptive,":[43],"ensemble-based":[45],"algorithms":[46],"that":[47,66,91],"can":[48],"improve":[49],"robustness":[51],"interpretability.":[53],"To":[54],"meet":[55],"demands,":[57],"this":[58],"paper":[59],"introduces":[60],"GA-SFS,":[61],"a":[62],"two-stage":[63],"hybrid":[64],"algorithm":[65],"combines":[67],"Genetic":[68],"Algorithms":[69],"(GA)":[70],"with":[71],"Sequential":[72],"Forward":[73],"Selection":[74],"(SFS)":[75],"to":[76],"select":[77],"informative":[78],"in":[80,98],"effectively.":[84],"Experimental":[85],"results":[86],"on":[87],"multiple":[88],"show":[90],"GA-SFS":[92],"outperforms":[93],"traditional":[94],"methods":[97],"classification":[99],"accuracy.":[100]},"counts_by_year":[{"year":2025,"cited_by_count":1}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}
