{"id":"https://openalex.org/W2994477952","doi":"https://doi.org/10.1109/kse.2019.8919337","title":"An Efficient Machine Learning Method to Solve Imbalanced Data in Metabolic Disease Prediction","display_name":"An Efficient Machine Learning Method to Solve Imbalanced Data in Metabolic Disease Prediction","publication_year":2019,"publication_date":"2019-10-01","ids":{"openalex":"https://openalex.org/W2994477952","doi":"https://doi.org/10.1109/kse.2019.8919337","mag":"2994477952"},"language":"en","primary_location":{"id":"doi:10.1109/kse.2019.8919337","is_oa":false,"landing_page_url":"https://doi.org/10.1109/kse.2019.8919337","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 11th International Conference on Knowledge and Systems Engineering (KSE)","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://orbilu.uni.lu/handle/10993/41512","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5066385222","display_name":"Vania Cecchini","orcid":null},"institutions":[{"id":"https://openalex.org/I186903577","display_name":"University of Luxembourg","ror":"https://ror.org/036x5ad56","country_code":"LU","type":"education","lineage":["https://openalex.org/I186903577"]}],"countries":["LU"],"is_corresponding":true,"raw_author_name":"Vania Cecchini","raw_affiliation_strings":["Life Sciences Research Unit, University of Luxembourg, Esch-sur-Alzette, Luxembourg"],"affiliations":[{"raw_affiliation_string":"Life Sciences Research Unit, University of Luxembourg, Esch-sur-Alzette, Luxembourg","institution_ids":["https://openalex.org/I186903577"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101929873","display_name":"Thanh\u2010Phuong Nguyen","orcid":"https://orcid.org/0000-0002-2368-1385"},"institutions":[{"id":"https://openalex.org/I186903577","display_name":"University of Luxembourg","ror":"https://ror.org/036x5ad56","country_code":"LU","type":"education","lineage":["https://openalex.org/I186903577"]}],"countries":["LU"],"is_corresponding":false,"raw_author_name":"Thanh-Phuong Nguyen","raw_affiliation_strings":["Megeno, Luxembourg Life Sciences Research Unit, University of Luxembourg"],"affiliations":[{"raw_affiliation_string":"Megeno, Luxembourg Life Sciences Research Unit, University of Luxembourg","institution_ids":["https://openalex.org/I186903577"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5012349487","display_name":"Thomas Pfau","orcid":"https://orcid.org/0000-0001-5048-2923"},"institutions":[{"id":"https://openalex.org/I186903577","display_name":"University of Luxembourg","ror":"https://ror.org/036x5ad56","country_code":"LU","type":"education","lineage":["https://openalex.org/I186903577"]}],"countries":["LU"],"is_corresponding":false,"raw_author_name":"Thomas Pfau","raw_affiliation_strings":["Life Sciences Research Unit, University of Luxembourg, Esch-sur-Alzette, Luxembourg"],"affiliations":[{"raw_affiliation_string":"Life Sciences Research Unit, University of Luxembourg, Esch-sur-Alzette, Luxembourg","institution_ids":["https://openalex.org/I186903577"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5082699450","display_name":"S\u00e9bastien De Landtsheer","orcid":"https://orcid.org/0000-0002-5421-2338"},"institutions":[{"id":"https://openalex.org/I186903577","display_name":"University of Luxembourg","ror":"https://ror.org/036x5ad56","country_code":"LU","type":"education","lineage":["https://openalex.org/I186903577"]}],"countries":["LU"],"is_corresponding":false,"raw_author_name":"Sebastien De Landtsheer","raw_affiliation_strings":["Life Sciences Research Unit, University of Luxembourg, Esch-sur-Alzette, Luxembourg"],"affiliations":[{"raw_affiliation_string":"Life Sciences Research Unit, University of Luxembourg, Esch-sur-Alzette, Luxembourg","institution_ids":["https://openalex.org/I186903577"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5050871083","display_name":"Thomas Sauter","orcid":"https://orcid.org/0000-0001-8225-2954"},"institutions":[{"id":"https://openalex.org/I186903577","display_name":"University of Luxembourg","ror":"https://ror.org/036x5ad56","country_code":"LU","type":"education","lineage":["https://openalex.org/I186903577"]}],"countries":["LU"],"is_corresponding":false,"raw_author_name":"Thomas Sauter","raw_affiliation_strings":["Life Sciences Research Unit, University of Luxembourg, Esch-sur-Alzette, Luxembourg"],"affiliations":[{"raw_affiliation_string":"Life Sciences Research Unit, University of Luxembourg, Esch-sur-Alzette, Luxembourg","institution_ids":["https://openalex.org/I186903577"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5066385222"],"corresponding_institution_ids":["https://openalex.org/I186903577"],"apc_list":null,"apc_paid":null,"fwci":0.1718,"has_fulltext":false,"cited_by_count":5,"citation_normalized_percentile":{"value":0.54127632,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"5"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10887","display_name":"Bioinformatics and Genomic Networks","score":0.9980999827384949,"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/T10887","display_name":"Bioinformatics and Genomic Networks","score":0.9980999827384949,"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/T12254","display_name":"Machine Learning in Bioinformatics","score":0.9933000206947327,"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/T10885","display_name":"Gene expression and cancer classification","score":0.9789000153541565,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.6687383055686951},{"id":"https://openalex.org/keywords/boosting","display_name":"Boosting (machine learning)","score":0.6438807845115662},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5843941569328308},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5781151056289673},{"id":"https://openalex.org/keywords/disease","display_name":"Disease","score":0.5698755383491516},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.41668862104415894},{"id":"https://openalex.org/keywords/computational-biology","display_name":"Computational biology","score":0.3226916790008545},{"id":"https://openalex.org/keywords/biology","display_name":"Biology","score":0.2157643735408783},{"id":"https://openalex.org/keywords/medicine","display_name":"Medicine","score":0.14167943596839905}],"concepts":[{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.6687383055686951},{"id":"https://openalex.org/C46686674","wikidata":"https://www.wikidata.org/wiki/Q466303","display_name":"Boosting (machine learning)","level":2,"score":0.6438807845115662},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5843941569328308},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5781151056289673},{"id":"https://openalex.org/C2779134260","wikidata":"https://www.wikidata.org/wiki/Q12136","display_name":"Disease","level":2,"score":0.5698755383491516},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.41668862104415894},{"id":"https://openalex.org/C70721500","wikidata":"https://www.wikidata.org/wiki/Q177005","display_name":"Computational biology","level":1,"score":0.3226916790008545},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.2157643735408783},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.14167943596839905},{"id":"https://openalex.org/C142724271","wikidata":"https://www.wikidata.org/wiki/Q7208","display_name":"Pathology","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/kse.2019.8919337","is_oa":false,"landing_page_url":"https://doi.org/10.1109/kse.2019.8919337","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 11th International Conference on Knowledge and Systems Engineering (KSE)","raw_type":"proceedings-article"},{"id":"pmh:oai:orbilu.uni.lu:10993/41512","is_oa":true,"landing_page_url":"https://orbilu.uni.lu/handle/10993/41512","pdf_url":null,"source":{"id":"https://openalex.org/S4306401815","display_name":"Open Repository and Bibliography (University of Luxembourg)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I186903577","host_organization_name":"University of Luxembourg","host_organization_lineage":["https://openalex.org/I186903577"],"host_organization_lineage_names":[],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"An Efficient Machine Learning Method to Solve Imbalanced Data in Metabolic Disease Prediction, 5 (2019); 2019 11TH INTERNATIONAL CONFERENCE ON KNOWLEDGE AND SYSTEMS ENGINEERING (KSE), Da Nang City, Vietnam [VN], from 24-10-2019 to 26-10-2019","raw_type":"peer reviewed"}],"best_oa_location":{"id":"pmh:oai:orbilu.uni.lu:10993/41512","is_oa":true,"landing_page_url":"https://orbilu.uni.lu/handle/10993/41512","pdf_url":null,"source":{"id":"https://openalex.org/S4306401815","display_name":"Open Repository and Bibliography (University of Luxembourg)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I186903577","host_organization_name":"University of Luxembourg","host_organization_lineage":["https://openalex.org/I186903577"],"host_organization_lineage_names":[],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"An Efficient Machine Learning Method to Solve Imbalanced Data in Metabolic Disease Prediction, 5 (2019); 2019 11TH INTERNATIONAL CONFERENCE ON KNOWLEDGE AND SYSTEMS ENGINEERING (KSE), Da Nang City, Vietnam [VN], from 24-10-2019 to 26-10-2019","raw_type":"peer reviewed"},"sustainable_development_goals":[{"display_name":"Good health and well-being","score":0.6299999952316284,"id":"https://metadata.un.org/sdg/3"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":31,"referenced_works":["https://openalex.org/W19051162","https://openalex.org/W129457532","https://openalex.org/W198362155","https://openalex.org/W1491708111","https://openalex.org/W1550699104","https://openalex.org/W1766594731","https://openalex.org/W1976937534","https://openalex.org/W1981267648","https://openalex.org/W1990315216","https://openalex.org/W2012140439","https://openalex.org/W2015918699","https://openalex.org/W2097532544","https://openalex.org/W2107710781","https://openalex.org/W2118978333","https://openalex.org/W2122863289","https://openalex.org/W2148143831","https://openalex.org/W2148502410","https://openalex.org/W2148722247","https://openalex.org/W2150767213","https://openalex.org/W2174734928","https://openalex.org/W2273011133","https://openalex.org/W2345356016","https://openalex.org/W2418959584","https://openalex.org/W2753509760","https://openalex.org/W2781702232","https://openalex.org/W2901568326","https://openalex.org/W2915536738","https://openalex.org/W2915806464","https://openalex.org/W6605134655","https://openalex.org/W6608060938","https://openalex.org/W6681922830"],"related_works":["https://openalex.org/W2125652721","https://openalex.org/W1540371141","https://openalex.org/W1549363203","https://openalex.org/W4231274751","https://openalex.org/W2154063878","https://openalex.org/W2556012038","https://openalex.org/W1489772951","https://openalex.org/W1518215897","https://openalex.org/W3082059448","https://openalex.org/W4313640622"],"abstract_inverted_index":{"The":[0,64,97,135],"increase":[1],"of":[2,11,34,61,100,107,121,172],"obesity,":[3],"its":[4],"related":[5,131],"diseases":[6,13,149],"and":[7,69,159],"the":[8,32,59,111,170],"high":[9],"incidence":[10],"metabolic":[12,36,55,133,154,174],"as":[14,82,157],"a":[15,18,24,104],"whole,":[16],"constitute":[17],"major":[19],"public":[20],"health":[21],"problem":[22,60],"on":[23],"global":[25],"scale.":[26],"New":[27],"strategies":[28,92],"that":[29,165],"allow":[30],"for":[31],"discovery":[33],"novel":[35,173],"disease-related":[37,175],"genes":[38],"are":[39],"necessary":[40],"to":[41,53,72,84,93,129,132,151,169],"develop":[42],"new":[43],"treatments.":[44],"In":[45],"this":[46,166],"paper,":[47],"we":[48,116],"proposed":[49],"an":[50],"efficient":[51],"method":[52,65,167],"predict":[54],"disease":[56],"genes,":[57,115],"solving":[58],"imbalanced":[62,95],"data.":[63],"combined":[66],"protein-protein":[67],"interactions":[68,71],"miRNA-target":[70],"construct":[73],"integrated":[74],"networks,":[75],"whose":[76],"topological":[77],"properties":[78],"can":[79],"be":[80,130],"used":[81],"features":[83],"train":[85],"machine":[86],"learning":[87],"classifiers.":[88],"We":[89],"applied":[90],"different":[91],"optimize":[94],"class.":[96],"best":[98],"model":[99,112],"gradient":[101],"boosting":[102],"achieved":[103],"significant":[105],"F1-score":[106],"0.82.":[108],"When":[109],"testing":[110],"with":[113,148,153],"non-disease":[114],"predicted":[117],"549":[118],"candidates,":[119],"out":[120],"which":[122],"123":[123],"were":[124,139],"validated":[125],"indirectly":[126],"from":[127],"literature":[128],"diseases.":[134],"remaining":[136],"genes'":[137],"functions":[138],"investigated":[140],"by":[141],"gene":[142],"enrichment":[143],"analysis,":[144],"revealing":[145],"their":[146],"association":[147],"known":[150],"co-occur":[152],"diseases,":[155],"such":[156],"cancer":[158],"cardiovascular":[160],"conditions.":[161],"These":[162],"results":[163],"indicated":[164],"contributed":[168],"identification":[171],"genes.":[176]},"counts_by_year":[{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":2}],"updated_date":"2026-04-04T16:13:02.066488","created_date":"2025-10-10T00:00:00"}