{"id":"https://openalex.org/W7123361422","doi":"https://doi.org/10.1109/dsa66321.2025.00057","title":"Individualized NIPT Timing via Regression and Dynamic Programming","display_name":"Individualized NIPT Timing via Regression and Dynamic Programming","publication_year":2025,"publication_date":"2025-11-24","ids":{"openalex":"https://openalex.org/W7123361422","doi":"https://doi.org/10.1109/dsa66321.2025.00057"},"language":null,"primary_location":{"id":"doi:10.1109/dsa66321.2025.00057","is_oa":false,"landing_page_url":"https://doi.org/10.1109/dsa66321.2025.00057","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 12th International Conference on Dependable Systems and Their Applications (DSA)","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/A5122906731","display_name":"Yixuan Li","orcid":null},"institutions":[{"id":"https://openalex.org/I4210109636","display_name":"NIHR Imperial Biomedical Research Centre","ror":"https://ror.org/01kmhx639","country_code":"GB","type":"facility","lineage":["https://openalex.org/I34931013","https://openalex.org/I4210109636"]},{"id":"https://openalex.org/I47508984","display_name":"Imperial College London","ror":"https://ror.org/041kmwe10","country_code":"GB","type":"education","lineage":["https://openalex.org/I47508984"]}],"countries":["GB"],"is_corresponding":true,"raw_author_name":"Yixuan Li","raw_affiliation_strings":["Imperial College London,Department of Biomedical Engineering,London,UK"],"affiliations":[{"raw_affiliation_string":"Imperial College London,Department of Biomedical Engineering,London,UK","institution_ids":["https://openalex.org/I4210109636","https://openalex.org/I47508984"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5122878562","display_name":"Yingkai Yuan","orcid":null},"institutions":[{"id":"https://openalex.org/I4210119942","display_name":"Wuhan Textile University","ror":"https://ror.org/02jgsf398","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210119942"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yingkai Yuan","raw_affiliation_strings":["School of Computer and Artificial Intelligence, Wuhan Textile University,Wuhan,China"],"affiliations":[{"raw_affiliation_string":"School of Computer and Artificial Intelligence, Wuhan Textile University,Wuhan,China","institution_ids":["https://openalex.org/I4210119942"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Zihan Wang","orcid":null},"institutions":[{"id":"https://openalex.org/I4210119942","display_name":"Wuhan Textile University","ror":"https://ror.org/02jgsf398","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210119942"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zihan Wang","raw_affiliation_strings":["School of Mathematics and Statistics, Wuhan Textile University,Wuhan,China"],"affiliations":[{"raw_affiliation_string":"School of Mathematics and Statistics, Wuhan Textile University,Wuhan,China","institution_ids":["https://openalex.org/I4210119942"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5059559776","display_name":"Yameng Feng","orcid":null},"institutions":[{"id":"https://openalex.org/I4210119942","display_name":"Wuhan Textile University","ror":"https://ror.org/02jgsf398","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210119942"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yameng Feng","raw_affiliation_strings":["School of Computer and Artificial Intelligence, Wuhan Textile University,Wuhan,China"],"affiliations":[{"raw_affiliation_string":"School of Computer and Artificial Intelligence, Wuhan Textile University,Wuhan,China","institution_ids":["https://openalex.org/I4210119942"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5122884113","display_name":"Chongguang Wu","orcid":null},"institutions":[{"id":"https://openalex.org/I4210119942","display_name":"Wuhan Textile University","ror":"https://ror.org/02jgsf398","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210119942"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chongguang Wu","raw_affiliation_strings":["School of Computer and Artificial Intelligence, Wuhan Textile University,Wuhan,China"],"affiliations":[{"raw_affiliation_string":"School of Computer and Artificial Intelligence, Wuhan Textile University,Wuhan,China","institution_ids":["https://openalex.org/I4210119942"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5122906731"],"corresponding_institution_ids":["https://openalex.org/I4210109636","https://openalex.org/I47508984"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.84390339,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"435","last_page":"442"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10978","display_name":"Prenatal Screening and Diagnostics","score":0.920799970626831,"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"}},"topics":[{"id":"https://openalex.org/T10978","display_name":"Prenatal Screening and Diagnostics","score":0.920799970626831,"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"}},{"id":"https://openalex.org/T12552","display_name":"Fetal and Pediatric Neurological Disorders","score":0.01979999989271164,"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"}},{"id":"https://openalex.org/T11213","display_name":"Genomic variations and chromosomal abnormalities","score":0.013399999588727951,"subfield":{"id":"https://openalex.org/subfields/1311","display_name":"Genetics"},"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/quantile-regression","display_name":"Quantile regression","score":0.5785999894142151},{"id":"https://openalex.org/keywords/polynomial-regression","display_name":"Polynomial regression","score":0.5084999799728394},{"id":"https://openalex.org/keywords/regression","display_name":"Regression","score":0.48030000925064087},{"id":"https://openalex.org/keywords/regression-analysis","display_name":"Regression analysis","score":0.4341999888420105},{"id":"https://openalex.org/keywords/lasso","display_name":"Lasso (programming language)","score":0.4296000003814697},{"id":"https://openalex.org/keywords/quadratic-programming","display_name":"Quadratic programming","score":0.4133000075817108},{"id":"https://openalex.org/keywords/linear-regression","display_name":"Linear regression","score":0.3549000024795532},{"id":"https://openalex.org/keywords/regularization","display_name":"Regularization (linguistics)","score":0.34540000557899475}],"concepts":[{"id":"https://openalex.org/C63817138","wikidata":"https://www.wikidata.org/wiki/Q3455889","display_name":"Quantile regression","level":2,"score":0.5785999894142151},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5544999837875366},{"id":"https://openalex.org/C120068334","wikidata":"https://www.wikidata.org/wiki/Q45343","display_name":"Polynomial regression","level":3,"score":0.5084999799728394},{"id":"https://openalex.org/C83546350","wikidata":"https://www.wikidata.org/wiki/Q1139051","display_name":"Regression","level":2,"score":0.48030000925064087},{"id":"https://openalex.org/C152877465","wikidata":"https://www.wikidata.org/wiki/Q208042","display_name":"Regression analysis","level":2,"score":0.4341999888420105},{"id":"https://openalex.org/C37616216","wikidata":"https://www.wikidata.org/wiki/Q3218363","display_name":"Lasso (programming language)","level":2,"score":0.4296000003814697},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.42910000681877136},{"id":"https://openalex.org/C81845259","wikidata":"https://www.wikidata.org/wiki/Q290117","display_name":"Quadratic programming","level":2,"score":0.4133000075817108},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3594000041484833},{"id":"https://openalex.org/C48921125","wikidata":"https://www.wikidata.org/wiki/Q10861030","display_name":"Linear regression","level":2,"score":0.3549000024795532},{"id":"https://openalex.org/C2776135515","wikidata":"https://www.wikidata.org/wiki/Q17143721","display_name":"Regularization (linguistics)","level":2,"score":0.34540000557899475},{"id":"https://openalex.org/C32220436","wikidata":"https://www.wikidata.org/wiki/Q2072214","display_name":"Personalized medicine","level":2,"score":0.3328999876976013},{"id":"https://openalex.org/C2780801425","wikidata":"https://www.wikidata.org/wiki/Q5164392","display_name":"Construct (python library)","level":2,"score":0.33000001311302185},{"id":"https://openalex.org/C110332635","wikidata":"https://www.wikidata.org/wiki/Q629498","display_name":"Genetic programming","level":2,"score":0.3034999966621399},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.302700012922287},{"id":"https://openalex.org/C45804977","wikidata":"https://www.wikidata.org/wiki/Q7239673","display_name":"Predictive modelling","level":2,"score":0.275299996137619},{"id":"https://openalex.org/C37404715","wikidata":"https://www.wikidata.org/wiki/Q380679","display_name":"Dynamic programming","level":2,"score":0.26980000734329224},{"id":"https://openalex.org/C118671147","wikidata":"https://www.wikidata.org/wiki/Q578714","display_name":"Quantile","level":2,"score":0.257999986410141},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.257099986076355},{"id":"https://openalex.org/C90119067","wikidata":"https://www.wikidata.org/wiki/Q43260","display_name":"Polynomial","level":2,"score":0.25699999928474426}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/dsa66321.2025.00057","is_oa":false,"landing_page_url":"https://doi.org/10.1109/dsa66321.2025.00057","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 12th International Conference on Dependable Systems and Their Applications (DSA)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/5","score":0.4743806719779968,"display_name":"Gender equality"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"With":[0],"the":[1,56,117,135,164,169,181],"widespread":[2],"adoption":[3],"of":[4,58],"Noninvasive":[5],"Prenatal":[6],"Testing":[7],"(NIPT),":[8],"selecting":[9,163],"an":[10,81],"appropriate":[11],"testing":[12,27,118,166],"time":[13,28,119],"has":[14,72,89,199],"become":[15],"critical":[16],"for":[17,124,177],"improving":[18],"test":[19],"accuracy.":[20],"This":[21],"study":[22],"proposes":[23],"a":[24,44,73,90,99,189],"personalized":[25,122,174,244],"NIPT":[26,165,237],"optimization":[29,205],"model":[30,46,133,171],"based":[31,215],"on":[32,62,77,104],"gestational":[33],"age":[34],"(GA)":[35],"and":[36,60,96,112,143,157,168,212,256],"body":[37],"mass":[38],"index":[39],"(BMI).":[40],"We":[41],"first":[42],"construct":[43],"predictive":[45],"combining":[47],"quadratic":[48],"polynomial":[49,210],"regression":[50,67,111,192,211],"with":[51,80,233],"Lasso":[52],"regularization":[53],"to":[54,115,141,221,258],"analyze":[55],"impact":[57],"GA":[59,71,85,95,156],"BMI":[61,88,97,129,158],"fetal":[63],"Y-chromosome":[64,78],"concentration.":[65],"The":[66,131],"results":[68,153],"show":[69,242],"that":[70,155,243],"significant":[74,91,100],"positive":[75],"effect":[76],"concentration,":[79],"accelerating":[82],"increase":[83],"as":[84,208],"grows,":[86],"whereas":[87],"negative":[92],"effect;":[93],"furthermore,":[94],"exhibit":[98],"interaction":[101],"effect.":[102],"Based":[103],"these":[105,230],"findings,":[106],"we":[107,241],"then":[108],"employ":[109],"quantile":[110],"dynamic":[113],"programming":[114],"optimize":[116],"point,":[120],"providing":[121],"recommendations":[123,176,246],"pregnant":[125],"women":[126],"at":[127],"different":[128],"levels.":[130],"optimized":[132],"reduces":[134],"overall":[136],"expected":[137],"risk":[138],"from":[139,236],"0.312":[140],"0.254":[142],"remains":[144],"robust":[145],"under":[146],"<tex":[147],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[148],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">$\\pm":[149],"1$</tex>-week":[150],"perturbations.":[151],"These":[152],"demonstrate":[154],"are":[159,247],"crucial":[160],"factors":[161],"in":[162,202,260],"time,":[167],"proposed":[170],"can":[172,218],"provide":[173],"testing-time":[175,245],"clinical":[178,223],"use.":[179],"Beyond":[180],"core":[182],"numerical":[183],"results,":[184],"this":[185],"work":[186],"illustrates":[187],"how":[188],"general":[190],"\u201d":[191],"explanation":[193],"-":[194,214],"probability":[195],"optimization\u201d":[196],"paradigm,":[197],"which":[198],"been":[200],"used":[201],"other":[203],"engineering":[204],"problems":[206],"such":[207],"evolutionary":[209],"dynamic-programming":[213],"control":[216],"strategies,":[217],"be":[219],"adapted":[220],"high-stakes":[222],"decision":[224],"making":[225],"[1]":[226],"[2].":[227],"By":[228],"connecting":[229],"methodological":[231],"ideas":[232],"large-scale":[234],"evidence":[235],"outcome":[238],"studies":[239],"[3],":[240],"not":[248],"only":[249],"statistically":[250],"sound":[251],"but":[252],"also":[253],"clinically":[254],"interpretable":[255],"feasible":[257],"implement":[259],"practice.":[261]},"counts_by_year":[],"updated_date":"2026-03-25T23:56:10.502304","created_date":"2026-01-14T00:00:00"}