{"id":"https://openalex.org/W4281728483","doi":"https://doi.org/10.1145/3523286.3524578","title":"Research on 10-year Beast Cancer Survival Prediction Model Based on Mixed Feature Selection","display_name":"Research on 10-year Beast Cancer Survival Prediction Model Based on Mixed Feature Selection","publication_year":2022,"publication_date":"2022-01-21","ids":{"openalex":"https://openalex.org/W4281728483","doi":"https://doi.org/10.1145/3523286.3524578"},"language":"en","primary_location":{"id":"doi:10.1145/3523286.3524578","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3523286.3524578","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 2nd International Conference on Bioinformatics and Intelligent Computing","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/A5076641805","display_name":"Yufang Deng","orcid":null},"institutions":[{"id":"https://openalex.org/I150807315","display_name":"Guangxi University","ror":"https://ror.org/02c9qn167","country_code":"CN","type":"education","lineage":["https://openalex.org/I150807315"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Yufang Deng","raw_affiliation_strings":["School of Computer, Guangxi University, China"],"affiliations":[{"raw_affiliation_string":"School of Computer, Guangxi University, China","institution_ids":["https://openalex.org/I150807315"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5076641805"],"corresponding_institution_ids":["https://openalex.org/I150807315"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.08575231,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"402","last_page":"407"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11396","display_name":"Artificial Intelligence in Healthcare","score":0.958299994468689,"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"}},"topics":[{"id":"https://openalex.org/T11396","display_name":"Artificial Intelligence in Healthcare","score":0.958299994468689,"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/T10885","display_name":"Gene expression and cancer classification","score":0.9286999702453613,"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/T12535","display_name":"Machine Learning and Data Classification","score":0.9207000136375427,"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":0.8023256063461304},{"id":"https://openalex.org/keywords/selection","display_name":"Selection (genetic algorithm)","score":0.6312831044197083},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6061103343963623},{"id":"https://openalex.org/keywords/genetic-algorithm","display_name":"Genetic algorithm","score":0.6038392186164856},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5764741897583008},{"id":"https://openalex.org/keywords/fitness-proportionate-selection","display_name":"Fitness proportionate selection","score":0.5666029453277588},{"id":"https://openalex.org/keywords/heuristic","display_name":"Heuristic","score":0.4993603229522705},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4584907591342926},{"id":"https://openalex.org/keywords/model-selection","display_name":"Model selection","score":0.44901981949806213},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4369056820869446},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.41625499725341797},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.3523266911506653},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3111363649368286},{"id":"https://openalex.org/keywords/fitness-function","display_name":"Fitness function","score":0.11789095401763916}],"concepts":[{"id":"https://openalex.org/C148483581","wikidata":"https://www.wikidata.org/wiki/Q446488","display_name":"Feature selection","level":2,"score":0.8023256063461304},{"id":"https://openalex.org/C81917197","wikidata":"https://www.wikidata.org/wiki/Q628760","display_name":"Selection (genetic algorithm)","level":2,"score":0.6312831044197083},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6061103343963623},{"id":"https://openalex.org/C8880873","wikidata":"https://www.wikidata.org/wiki/Q187787","display_name":"Genetic algorithm","level":2,"score":0.6038392186164856},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5764741897583008},{"id":"https://openalex.org/C99701942","wikidata":"https://www.wikidata.org/wiki/Q5455479","display_name":"Fitness proportionate selection","level":4,"score":0.5666029453277588},{"id":"https://openalex.org/C173801870","wikidata":"https://www.wikidata.org/wiki/Q201413","display_name":"Heuristic","level":2,"score":0.4993603229522705},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4584907591342926},{"id":"https://openalex.org/C93959086","wikidata":"https://www.wikidata.org/wiki/Q6888345","display_name":"Model selection","level":2,"score":0.44901981949806213},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4369056820869446},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.41625499725341797},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3523266911506653},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3111363649368286},{"id":"https://openalex.org/C176066374","wikidata":"https://www.wikidata.org/wiki/Q629118","display_name":"Fitness function","level":3,"score":0.11789095401763916},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3523286.3524578","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3523286.3524578","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 2nd International Conference on Bioinformatics and Intelligent Computing","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Good health and well-being","id":"https://metadata.un.org/sdg/3","score":0.800000011920929}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":7,"referenced_works":["https://openalex.org/W748373178","https://openalex.org/W1971361999","https://openalex.org/W2042899522","https://openalex.org/W2530103281","https://openalex.org/W2773328008","https://openalex.org/W2952183584","https://openalex.org/W3021925134"],"related_works":["https://openalex.org/W2545929163","https://openalex.org/W2352457515","https://openalex.org/W2350426988","https://openalex.org/W10353878","https://openalex.org/W2398812955","https://openalex.org/W4200573379","https://openalex.org/W1480497081","https://openalex.org/W2135808265","https://openalex.org/W2037594302","https://openalex.org/W2377360380"],"abstract_inverted_index":{"On":[0],"the":[1,4,13,16,23,66,73,82,104,125,134],"basis":[2],"of":[3,35,69,75,122,145,158],"breast":[5,96],"cancer":[6,97],"data":[7,105],"from":[8,108],"1973":[9],"to":[10,48,62,64,88,111,157],"2015":[11],"in":[12,120],"SEER":[14],"database,":[15],"optimal":[17],"feature":[18,25,29,116],"selection":[19,26,30,117],"is":[20,32,46,60,86,106,131,155],"based":[21],"on":[22],"hybrid":[24,115],"algorithm.":[27,41],"Hybrid":[28],"algorithm":[31,59,85],"a":[33,90],"combination":[34,68],"filtering":[36],"method":[37,130],"and":[38,54,77,119,143,151],"heuristic":[39],"search":[40,63],"First,":[42],"chi-square":[43],"test":[44],"(chi)":[45],"used":[47,61,87],"filter":[49],"redundant":[50],"or":[51],"irrelevant":[52],"features,":[53],"then":[55],"an":[56],"improved":[57,72,78],"genetic":[58],"find":[65],"best":[67],"features.":[70,139],"Mainly":[71],"formulation":[74],"fitness":[76],"roulette":[79],"selection.":[80],"Then":[81],"XGBoost":[83],"classification":[84],"establish":[89],"10-year":[91],"survival":[92],"prediction":[93],"model":[94,126,135,147],"for":[95],"patients.":[98],"The":[99,140],"experimental":[100],"result":[101],"show":[102],"that":[103],"reduced":[107],"22-dimensional":[109],"features":[110],"6-dimensional":[112],"by":[113,128,137],"using":[114],"method,":[118],"terms":[121],"five":[123],"indicators,":[124],"established":[127,136],"this":[129,146],"better":[132],"than":[133],"all":[138,159],"accuracy,":[141],"precision":[142],"AUC":[144],"are":[148],"0.8468,":[149],"0.8385,":[150],"0.8181":[152],"respectively,":[153],"which":[154],"superior":[156],"other":[160],"models.":[161]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
