{"id":"https://openalex.org/W2402089432","doi":"https://doi.org/10.1109/icnsc.2016.7479016","title":"A data-driven approach to predict Small-for-Gestational-Age infants","display_name":"A data-driven approach to predict Small-for-Gestational-Age infants","publication_year":2016,"publication_date":"2016-04-01","ids":{"openalex":"https://openalex.org/W2402089432","doi":"https://doi.org/10.1109/icnsc.2016.7479016","mag":"2402089432"},"language":"en","primary_location":{"id":"doi:10.1109/icnsc.2016.7479016","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icnsc.2016.7479016","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 IEEE 13th International Conference on Networking, Sensing, and Control (ICNSC)","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/A5100738628","display_name":"Jingchao Sun","orcid":"https://orcid.org/0000-0001-8360-2282"},"institutions":[{"id":"https://openalex.org/I37796252","display_name":"Beijing University of Technology","ror":"https://ror.org/037b1pp87","country_code":"CN","type":"education","lineage":["https://openalex.org/I37796252"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Jingchao Sun","raw_affiliation_strings":["School of Software Engineering, Beijing University of Technology, Beijing, China"],"affiliations":[{"raw_affiliation_string":"School of Software Engineering, Beijing University of Technology, Beijing, China","institution_ids":["https://openalex.org/I37796252"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100396472","display_name":"Lu Liu","orcid":"https://orcid.org/0000-0002-0722-9241"},"institutions":[{"id":"https://openalex.org/I37796252","display_name":"Beijing University of Technology","ror":"https://ror.org/037b1pp87","country_code":"CN","type":"education","lineage":["https://openalex.org/I37796252"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lu Liu","raw_affiliation_strings":["School of Software Engineering, Beijing University of Technology, Beijing, China"],"affiliations":[{"raw_affiliation_string":"School of Software Engineering, Beijing University of Technology, Beijing, China","institution_ids":["https://openalex.org/I37796252"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100393880","display_name":"Jianqiang Li","orcid":"https://orcid.org/0000-0003-1995-9249"},"institutions":[{"id":"https://openalex.org/I37796252","display_name":"Beijing University of Technology","ror":"https://ror.org/037b1pp87","country_code":"CN","type":"education","lineage":["https://openalex.org/I37796252"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jianqiang Li","raw_affiliation_strings":["School of Software Engineering, Beijing University of Technology, Beijing, China"],"affiliations":[{"raw_affiliation_string":"School of Software Engineering, Beijing University of Technology, Beijing, China","institution_ids":["https://openalex.org/I37796252"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5050950280","display_name":"Ji\u2010Jiang Yang","orcid":"https://orcid.org/0000-0002-4124-6408"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ji-jiang Yang","raw_affiliation_strings":["Research Institute of Information Technology, Tsinghua University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Research Institute of Information Technology, Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5025830923","display_name":"Chen Shi","orcid":"https://orcid.org/0000-0002-5192-5172"},"institutions":[{"id":"https://openalex.org/I2801228662","display_name":"Peking Union Medical College Hospital","ror":"https://ror.org/04jztag35","country_code":"CN","type":"healthcare","lineage":["https://openalex.org/I2801228662"]},{"id":"https://openalex.org/I200296433","display_name":"Chinese Academy of Medical Sciences & Peking Union Medical College","ror":"https://ror.org/02drdmm93","country_code":"CN","type":"education","lineage":["https://openalex.org/I200296433"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shi Chen","raw_affiliation_strings":["Dept. of Endocrinology, Peking Union Medical College Hospital, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Dept. of Endocrinology, Peking Union Medical College Hospital, Beijing, China","institution_ids":["https://openalex.org/I2801228662","https://openalex.org/I200296433"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100434842","display_name":"Qing Wang","orcid":"https://orcid.org/0000-0002-5526-7154"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qing Wang","raw_affiliation_strings":["Research Institute of Information Technology, Tsinghua University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Research Institute of Information Technology, Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5081318069","display_name":"MengChu Zhou","orcid":"https://orcid.org/0000-0002-5408-8752"},"institutions":[{"id":"https://openalex.org/I118118575","display_name":"New Jersey Institute of Technology","ror":"https://ror.org/05e74xb87","country_code":"US","type":"education","lineage":["https://openalex.org/I118118575"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Mengchu Zhou","raw_affiliation_strings":["Department of Electrical and Computer Engineering, New Jersey Institute of Technology, Newark, USA"],"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, New Jersey Institute of Technology, Newark, USA","institution_ids":["https://openalex.org/I118118575"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5060892208","display_name":"Rong Lia","orcid":null},"institutions":[{"id":"https://openalex.org/I37796252","display_name":"Beijing University of Technology","ror":"https://ror.org/037b1pp87","country_code":"CN","type":"education","lineage":["https://openalex.org/I37796252"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Rong Lia","raw_affiliation_strings":["Beijing University of Technology, Beijing, CN"],"affiliations":[{"raw_affiliation_string":"Beijing University of Technology, Beijing, CN","institution_ids":["https://openalex.org/I37796252"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100461634","display_name":"Bo Liu","orcid":"https://orcid.org/0000-0002-2393-117X"},"institutions":[{"id":"https://openalex.org/I37796252","display_name":"Beijing University of Technology","ror":"https://ror.org/037b1pp87","country_code":"CN","type":"education","lineage":["https://openalex.org/I37796252"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Bo Liu","raw_affiliation_strings":["School of Software Engineering, Beijing University of Technology, Beijing, China"],"affiliations":[{"raw_affiliation_string":"School of Software Engineering, Beijing University of Technology, Beijing, China","institution_ids":["https://openalex.org/I37796252"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5057935426","display_name":"Jing Bi","orcid":"https://orcid.org/0000-0002-4610-0141"},"institutions":[{"id":"https://openalex.org/I37796252","display_name":"Beijing University of Technology","ror":"https://ror.org/037b1pp87","country_code":"CN","type":"education","lineage":["https://openalex.org/I37796252"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jing Bi","raw_affiliation_strings":["School of Software Engineering, Beijing University of Technology, Beijing, China"],"affiliations":[{"raw_affiliation_string":"School of Software Engineering, Beijing University of Technology, Beijing, China","institution_ids":["https://openalex.org/I37796252"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":10,"corresponding_author_ids":["https://openalex.org/A5100738628"],"corresponding_institution_ids":["https://openalex.org/I37796252"],"apc_list":null,"apc_paid":null,"fwci":0.2873,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.69044975,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":"95","issue":null,"first_page":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10866","display_name":"Nutritional Studies and Diet","score":0.9459999799728394,"subfield":{"id":"https://openalex.org/subfields/2739","display_name":"Public Health, Environmental and Occupational Health"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},"topics":[{"id":"https://openalex.org/T10866","display_name":"Nutritional Studies and Diet","score":0.9459999799728394,"subfield":{"id":"https://openalex.org/subfields/2739","display_name":"Public Health, Environmental and Occupational Health"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},{"id":"https://openalex.org/T10673","display_name":"Gestational Diabetes Research and Management","score":0.9383000135421753,"subfield":{"id":"https://openalex.org/subfields/2729","display_name":"Obstetrics and Gynecology"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},{"id":"https://openalex.org/T11184","display_name":"Neonatal and fetal brain pathology","score":0.9297999739646912,"subfield":{"id":"https://openalex.org/subfields/2735","display_name":"Pediatrics, Perinatology and Child 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/computer-science","display_name":"Computer science","score":0.7307803630828857},{"id":"https://openalex.org/keywords/random-forest","display_name":"Random forest","score":0.7103485465049744},{"id":"https://openalex.org/keywords/feature-selection","display_name":"Feature selection","score":0.7016563415527344},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5931313633918762},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5644614696502686},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.5370176434516907},{"id":"https://openalex.org/keywords/construct","display_name":"Construct (python library)","score":0.4996960163116455},{"id":"https://openalex.org/keywords/logistic-regression","display_name":"Logistic regression","score":0.47914737462997437},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.47701382637023926},{"id":"https://openalex.org/keywords/receiver-operating-characteristic","display_name":"Receiver operating characteristic","score":0.47133326530456543},{"id":"https://openalex.org/keywords/selection","display_name":"Selection (genetic algorithm)","score":0.44865861535072327},{"id":"https://openalex.org/keywords/small-for-gestational-age","display_name":"Small for gestational age","score":0.4419914484024048},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.43151891231536865},{"id":"https://openalex.org/keywords/small-data","display_name":"Small data","score":0.4247409701347351},{"id":"https://openalex.org/keywords/feature-engineering","display_name":"Feature engineering","score":0.41442063450813293},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.13697382807731628},{"id":"https://openalex.org/keywords/gestational-age","display_name":"Gestational age","score":0.09351512789726257}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7307803630828857},{"id":"https://openalex.org/C169258074","wikidata":"https://www.wikidata.org/wiki/Q245748","display_name":"Random forest","level":2,"score":0.7103485465049744},{"id":"https://openalex.org/C148483581","wikidata":"https://www.wikidata.org/wiki/Q446488","display_name":"Feature selection","level":2,"score":0.7016563415527344},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5931313633918762},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5644614696502686},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.5370176434516907},{"id":"https://openalex.org/C2780801425","wikidata":"https://www.wikidata.org/wiki/Q5164392","display_name":"Construct (python library)","level":2,"score":0.4996960163116455},{"id":"https://openalex.org/C151956035","wikidata":"https://www.wikidata.org/wiki/Q1132755","display_name":"Logistic regression","level":2,"score":0.47914737462997437},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.47701382637023926},{"id":"https://openalex.org/C58471807","wikidata":"https://www.wikidata.org/wiki/Q327120","display_name":"Receiver operating characteristic","level":2,"score":0.47133326530456543},{"id":"https://openalex.org/C81917197","wikidata":"https://www.wikidata.org/wiki/Q628760","display_name":"Selection (genetic algorithm)","level":2,"score":0.44865861535072327},{"id":"https://openalex.org/C2780938740","wikidata":"https://www.wikidata.org/wiki/Q1298973","display_name":"Small for gestational age","level":4,"score":0.4419914484024048},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.43151891231536865},{"id":"https://openalex.org/C2779280203","wikidata":"https://www.wikidata.org/wiki/Q17121211","display_name":"Small data","level":2,"score":0.4247409701347351},{"id":"https://openalex.org/C2778827112","wikidata":"https://www.wikidata.org/wiki/Q22245680","display_name":"Feature engineering","level":3,"score":0.41442063450813293},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.13697382807731628},{"id":"https://openalex.org/C2778376644","wikidata":"https://www.wikidata.org/wiki/Q2253111","display_name":"Gestational age","level":3,"score":0.09351512789726257},{"id":"https://openalex.org/C2779234561","wikidata":"https://www.wikidata.org/wiki/Q11995","display_name":"Pregnancy","level":2,"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/C54355233","wikidata":"https://www.wikidata.org/wiki/Q7162","display_name":"Genetics","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/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icnsc.2016.7479016","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icnsc.2016.7479016","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 IEEE 13th International Conference on Networking, Sensing, and Control (ICNSC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Life in Land","score":0.5299999713897705,"id":"https://metadata.un.org/sdg/15"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":24,"referenced_works":["https://openalex.org/W161457750","https://openalex.org/W1495061682","https://openalex.org/W1602699467","https://openalex.org/W1751977842","https://openalex.org/W1923635693","https://openalex.org/W2015878565","https://openalex.org/W2053090063","https://openalex.org/W2060947741","https://openalex.org/W2071817951","https://openalex.org/W2074280418","https://openalex.org/W2096274362","https://openalex.org/W2101234009","https://openalex.org/W2120719282","https://openalex.org/W2141014056","https://openalex.org/W2154053567","https://openalex.org/W2188911764","https://openalex.org/W2411462260","https://openalex.org/W2463849692","https://openalex.org/W2799148064","https://openalex.org/W2911964244","https://openalex.org/W4242841269","https://openalex.org/W6640004956","https://openalex.org/W6675354045","https://openalex.org/W6678290713"],"related_works":["https://openalex.org/W3193043704","https://openalex.org/W4386259002","https://openalex.org/W1546989560","https://openalex.org/W3171520305","https://openalex.org/W4388745254","https://openalex.org/W2980082554","https://openalex.org/W1517228774","https://openalex.org/W2767419625","https://openalex.org/W2389704471","https://openalex.org/W4360615883"],"abstract_inverted_index":{"This":[0,88],"work":[1,89,153],"studies":[2],"the":[3,49,97,127,141,145,165,173,176,180,184],"problem":[4],"of":[5,9,52,122,129,140],"identifying":[6],"risk":[7,50,98],"factors":[8,51,99,157,161],"Small":[10],"for":[11,18],"Gestational":[12],"Age":[13],"(SGA)":[14],"and":[15,27,76,110,113,124,158,162,170],"building":[16],"classifiers":[17],"SGA":[19,22,53,68],"prediction.":[20],"Recently,":[21],"infants":[23],"have":[24,45,61,74],"received":[25],"more":[26,28],"concerns":[29],"as":[30,78],"this":[31,152],"illness":[32],"brings":[33],"many":[34],"difficulties":[35],"to":[36,47,66,82],"them":[37,115],"along":[38],"with":[39,86],"their":[40],"whole":[41],"life.":[42],"Some":[43],"experts":[44],"begun":[46],"study":[48],"onset":[54],"by":[55],"using":[56],"traditional":[57],"statistical":[58],"ways.":[59],"Others":[60],"used":[62],"logistic":[63],"regression":[64],"(LR)":[65],"construct":[67],"prediction":[69],"models.":[70],"Meanwhile,":[71],"machine":[72],"learning":[73],"evolved":[75],"envisioned":[77],"a":[79],"tool":[80],"able":[81],"potentially":[83],"identify":[84],"babies":[85],"SGA.":[87],"tests":[90],"several":[91],"feature":[92,147,166],"selection":[93,148,167],"methods.":[94],"Based":[95],"on":[96,183],"obtained":[100],"through":[101],"them,":[102],"it":[103],"trains":[104],"support":[105],"vector":[106],"machine,":[107],"random":[108],"forest,":[109],"LR":[111,139,177],"models":[112],"evaluates":[114],"via":[116],"10-fold":[117],"cross":[118],"validation":[119],"in":[120],"terms":[121],"precision":[123],"area":[125],"under":[126],"curve":[128],"receiver":[130],"operator":[131],"characteristic":[132],"curve.":[133],"The":[134],"results":[135],"show":[136],"that":[137,164],"sparse":[138],"wrapper":[142],"algorithms":[143],"owns":[144],"best":[146,181],"effectiveness.":[149],"In":[150],"addition,":[151],"compares":[154],"data":[155,185],"driven":[156,160,186],"knowledge":[159],"shows":[163],"is":[168],"necessary":[169],"effective.":[171],"Among":[172],"trained":[174],"classifiers,":[175],"model":[178],"achieves":[179],"performance":[182],"factors.":[187]},"counts_by_year":[{"year":2022,"cited_by_count":1},{"year":2018,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}