{"id":"https://openalex.org/W3179186621","doi":"https://doi.org/10.1109/memea52024.2021.9478696","title":"Biological Data Classification via Faster MAXimum Feasible Subsystem Algorithm","display_name":"Biological Data Classification via Faster MAXimum Feasible Subsystem Algorithm","publication_year":2021,"publication_date":"2021-06-23","ids":{"openalex":"https://openalex.org/W3179186621","doi":"https://doi.org/10.1109/memea52024.2021.9478696","mag":"3179186621"},"language":"en","primary_location":{"id":"doi:10.1109/memea52024.2021.9478696","is_oa":false,"landing_page_url":"https://doi.org/10.1109/memea52024.2021.9478696","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE International Symposium on Medical Measurements and Applications (MeMeA)","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/A5008690016","display_name":"Fereshteh Fakhar Firouzeh","orcid":"https://orcid.org/0000-0003-3720-5192"},"institutions":[{"id":"https://openalex.org/I67031392","display_name":"Carleton University","ror":"https://ror.org/02qtvee93","country_code":"CA","type":"education","lineage":["https://openalex.org/I67031392"]}],"countries":["CA"],"is_corresponding":true,"raw_author_name":"Fereshteh Fakhar Firouzeh","raw_affiliation_strings":["Carleton University,Faculty of Engineering,Systems and Computer Engineering Department,Ottawa,Canada"],"affiliations":[{"raw_affiliation_string":"Carleton University,Faculty of Engineering,Systems and Computer Engineering Department,Ottawa,Canada","institution_ids":["https://openalex.org/I67031392"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5052753072","display_name":"John W. Chinneck","orcid":"https://orcid.org/0000-0002-8744-4653"},"institutions":[{"id":"https://openalex.org/I67031392","display_name":"Carleton University","ror":"https://ror.org/02qtvee93","country_code":"CA","type":"education","lineage":["https://openalex.org/I67031392"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"John W. Chinneck","raw_affiliation_strings":["Carleton University,Faculty of Engineering,Systems and Computer Engineering Department,Ottawa,Canada"],"affiliations":[{"raw_affiliation_string":"Carleton University,Faculty of Engineering,Systems and Computer Engineering Department,Ottawa,Canada","institution_ids":["https://openalex.org/I67031392"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5012603099","display_name":"Sreeraman Rajan","orcid":"https://orcid.org/0000-0003-0153-6723"},"institutions":[{"id":"https://openalex.org/I67031392","display_name":"Carleton University","ror":"https://ror.org/02qtvee93","country_code":"CA","type":"education","lineage":["https://openalex.org/I67031392"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Sreeraman Rajan","raw_affiliation_strings":["Carleton University,Faculty of Engineering,Systems and Computer Engineering Department,Ottawa,Canada"],"affiliations":[{"raw_affiliation_string":"Carleton University,Faculty of Engineering,Systems and Computer Engineering Department,Ottawa,Canada","institution_ids":["https://openalex.org/I67031392"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5008690016"],"corresponding_institution_ids":["https://openalex.org/I67031392"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.08792354,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"160","issue":null,"first_page":"1","last_page":"5"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12535","display_name":"Machine Learning and Data Classification","score":0.9979000091552734,"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"}},"topics":[{"id":"https://openalex.org/T12535","display_name":"Machine Learning and Data Classification","score":0.9979000091552734,"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"}},{"id":"https://openalex.org/T12254","display_name":"Machine Learning in Bioinformatics","score":0.9944999814033508,"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/T12072","display_name":"Machine Learning and Algorithms","score":0.9901999831199646,"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/hyperparameter","display_name":"Hyperparameter","score":0.738397479057312},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6816658973693848},{"id":"https://openalex.org/keywords/naive-bayes-classifier","display_name":"Naive Bayes classifier","score":0.6793473958969116},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.6768420934677124},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.62671959400177},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.568320095539093},{"id":"https://openalex.org/keywords/statistical-classification","display_name":"Statistical classification","score":0.4792349636554718},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.4726411700248718},{"id":"https://openalex.org/keywords/precision-and-recall","display_name":"Precision and recall","score":0.43265533447265625},{"id":"https://openalex.org/keywords/logistic-regression","display_name":"Logistic regression","score":0.4105128049850464},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3748512864112854}],"concepts":[{"id":"https://openalex.org/C8642999","wikidata":"https://www.wikidata.org/wiki/Q4171168","display_name":"Hyperparameter","level":2,"score":0.738397479057312},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6816658973693848},{"id":"https://openalex.org/C52001869","wikidata":"https://www.wikidata.org/wiki/Q812530","display_name":"Naive Bayes classifier","level":3,"score":0.6793473958969116},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.6768420934677124},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.62671959400177},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.568320095539093},{"id":"https://openalex.org/C110083411","wikidata":"https://www.wikidata.org/wiki/Q1744628","display_name":"Statistical classification","level":2,"score":0.4792349636554718},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4726411700248718},{"id":"https://openalex.org/C81669768","wikidata":"https://www.wikidata.org/wiki/Q2359161","display_name":"Precision and recall","level":2,"score":0.43265533447265625},{"id":"https://openalex.org/C151956035","wikidata":"https://www.wikidata.org/wiki/Q1132755","display_name":"Logistic regression","level":2,"score":0.4105128049850464},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3748512864112854}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/memea52024.2021.9478696","is_oa":false,"landing_page_url":"https://doi.org/10.1109/memea52024.2021.9478696","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE International Symposium on Medical Measurements and Applications (MeMeA)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Peace, Justice and strong institutions","id":"https://metadata.un.org/sdg/16","score":0.6700000166893005}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":30,"referenced_works":["https://openalex.org/W7083549","https://openalex.org/W1597806057","https://openalex.org/W1873332500","https://openalex.org/W2082030917","https://openalex.org/W2101234009","https://openalex.org/W2330219538","https://openalex.org/W2547480331","https://openalex.org/W2610136582","https://openalex.org/W2808391149","https://openalex.org/W2918821272","https://openalex.org/W2948135333","https://openalex.org/W2999812538","https://openalex.org/W3017922080","https://openalex.org/W3023211159","https://openalex.org/W3024371423","https://openalex.org/W3041589471","https://openalex.org/W3045004532","https://openalex.org/W3094934854","https://openalex.org/W3098394437","https://openalex.org/W3120740533","https://openalex.org/W3128431169","https://openalex.org/W3214916883","https://openalex.org/W4213102919","https://openalex.org/W4385486483","https://openalex.org/W6635943106","https://openalex.org/W6639175750","https://openalex.org/W6675354045","https://openalex.org/W6729429595","https://openalex.org/W6780568522","https://openalex.org/W6790325568"],"related_works":["https://openalex.org/W4317422759","https://openalex.org/W4385770464","https://openalex.org/W2086889680","https://openalex.org/W4224262160","https://openalex.org/W4388878085","https://openalex.org/W3153505674","https://openalex.org/W4246466849","https://openalex.org/W4388878069","https://openalex.org/W2997511728","https://openalex.org/W2525967854"],"abstract_inverted_index":{"Machine":[0],"Learning":[1],"(ML)":[2],"techniques":[3],"are":[4],"the":[5,69,83,115,128],"foundation":[6],"of":[7,19],"many":[8],"next-generation":[9],"technologies":[10],"and":[11,25,31,101,117,151],"have":[12],"been":[13],"swiftly":[14],"adopted":[15],"in":[16,21,37,48,82,111],"a":[17,56],"variety":[18],"applications":[20],"healthcare":[22],"from":[23,55],"prognosis":[24],"medical":[26],"diagnosis":[27],"to":[28,78,135],"personalized":[29],"treatment":[30],"drug":[32],"manufacturing.":[33],"A":[34],"central":[35],"model":[36],"ML":[38,123],"is":[39,76,89],"classification,":[40],"an":[41,62],"important":[42],"tool":[43],"for":[44,68,121],"intelligent":[45],"decision":[46],"making":[47],"medicine":[49],"such":[50,139],"as":[51,140],"distinguishing":[52],"ill":[53],"patients":[54],"normal":[57],"population.":[58],"In":[59],"this":[60],"paper,":[61],"algorithm":[63],"using":[64,97],"improved":[65],"solution":[66],"methods":[67],"MAXimum":[70],"Feasible":[71],"Subsystem":[72],"(MAX":[73],"FS)":[74],"problem":[75],"applied":[77],"biological":[79],"classification":[80,95],"problems":[81],"UCI":[84],"database.":[85],"The":[86,105],"proposed":[87,106],"method":[88,107],"compared":[90,134],"with":[91,100],"four":[92],"widely":[93],"used":[94],"models":[96],"10-fold":[98],"cross-validation":[99],"without":[102],"hyperparameter":[103],"tuning.":[104],"provides":[108],"higher":[109],"accuracy":[110],"more":[112],"cases":[113],"than":[114],"comparators":[116],"shows":[118],"promising":[119],"results":[120],"recall-oriented":[122],"tasks":[124],"since":[125],"it":[126],"improves":[127],"average":[129],"recall":[130],"by":[131],"17%":[132],"when":[133],"other":[136],"well-known":[137],"classifiers":[138],"K-Nearest":[141],"Neighbours":[142],"(KNN),":[143],"Support":[144],"Vector":[145],"Machines":[146],"(SVM),":[147],"Naive":[148],"Bayes":[149],"(NB),":[150],"Logistic":[152],"Regression":[153],"(LR).":[154]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
