{"id":"https://openalex.org/W4392025230","doi":"https://doi.org/10.1109/aipr60534.2023.10440689","title":"Generation of Synthetic Data for Medical Decision Support Applications","display_name":"Generation of Synthetic Data for Medical Decision Support Applications","publication_year":2023,"publication_date":"2023-09-27","ids":{"openalex":"https://openalex.org/W4392025230","doi":"https://doi.org/10.1109/aipr60534.2023.10440689"},"language":"en","primary_location":{"id":"doi:10.1109/aipr60534.2023.10440689","is_oa":false,"landing_page_url":"https://doi.org/10.1109/aipr60534.2023.10440689","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 IEEE Applied Imagery Pattern Recognition Workshop (AIPR)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5093976649","display_name":"Kenneth Hydock","orcid":null},"institutions":[{"id":"https://openalex.org/I128365640","display_name":"Regis University","ror":"https://ror.org/043ae9h44","country_code":"US","type":"education","lineage":["https://openalex.org/I128365640"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Kenneth Hydock","raw_affiliation_strings":["Regis University,Dept. of Data Science,Denver,CO,USA","Dept. of Data Science, Regis University, Denver, CO, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Regis University,Dept. of Data Science,Denver,CO,USA","institution_ids":["https://openalex.org/I128365640"]},{"raw_affiliation_string":"Dept. of Data Science, Regis University, Denver, CO, USA","institution_ids":["https://openalex.org/I128365640"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5008366004","display_name":"Andrea Elliott","orcid":"https://orcid.org/0000-0002-3969-6848"},"institutions":[{"id":"https://openalex.org/I128365640","display_name":"Regis University","ror":"https://ror.org/043ae9h44","country_code":"US","type":"education","lineage":["https://openalex.org/I128365640"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Andrea Elliott","raw_affiliation_strings":["Regis University,Dept. of Data Science,Denver,CO,USA","Dept. of Data Science, Regis University, Denver, CO, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Regis University,Dept. of Data Science,Denver,CO,USA","institution_ids":["https://openalex.org/I128365640"]},{"raw_affiliation_string":"Dept. of Data Science, Regis University, Denver, CO, USA","institution_ids":["https://openalex.org/I128365640"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5109883060","display_name":"Mike Busch","orcid":null},"institutions":[{"id":"https://openalex.org/I128365640","display_name":"Regis University","ror":"https://ror.org/043ae9h44","country_code":"US","type":"education","lineage":["https://openalex.org/I128365640"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Mike Busch","raw_affiliation_strings":["Regis University,Dept. of Data Science,Denver,CO,USA","Dept. of Data Science, Regis University, Denver, CO, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Regis University,Dept. of Data Science,Denver,CO,USA","institution_ids":["https://openalex.org/I128365640"]},{"raw_affiliation_string":"Dept. of Data Science, Regis University, Denver, CO, USA","institution_ids":["https://openalex.org/I128365640"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5093976650","display_name":"Lauren Lipchak","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Lauren Lipchak","raw_affiliation_strings":["Sculptor of Systems SimWerx,Denver,CO,USA","Sculptor of Systems SimWerx, Denver, CO, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Sculptor of Systems SimWerx,Denver,CO,USA","institution_ids":[]},{"raw_affiliation_string":"Sculptor of Systems SimWerx, Denver, CO, USA","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5093976651","display_name":"Daniel Blair","orcid":null},"institutions":[{"id":"https://openalex.org/I4210117836","display_name":"Space Micro (United States)","ror":"https://ror.org/03bc0qh53","country_code":"US","type":"company","lineage":["https://openalex.org/I4210117836"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Daniel Blair","raw_affiliation_strings":["Bit Space Development XR,Winnepeg,CA","Bit Space Development XR, Winnepeg, CA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Bit Space Development XR,Winnepeg,CA","institution_ids":["https://openalex.org/I4210117836"]},{"raw_affiliation_string":"Bit Space Development XR, Winnepeg, CA","institution_ids":["https://openalex.org/I4210117836"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5107345722","display_name":"J. D. Chapman","orcid":"https://orcid.org/0000-0002-2926-8962"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"John Chapman","raw_affiliation_strings":["Architect of Connections Simwerx,Denver,CO,USA","Architect of Connections Simwerx, Denver, CO, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Architect of Connections Simwerx,Denver,CO,USA","institution_ids":[]},{"raw_affiliation_string":"Architect of Connections Simwerx, Denver, CO, USA","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.3641,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.69436304,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":96,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"7"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10444","display_name":"Context-Aware Activity Recognition Systems","score":0.9812999963760376,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/T10444","display_name":"Context-Aware Activity Recognition Systems","score":0.9812999963760376,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/T11396","display_name":"Artificial Intelligence in Healthcare","score":0.9729999899864197,"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/T12205","display_name":"Time Series Analysis and Forecasting","score":0.9714999794960022,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/computer-science","display_name":"Computer science","score":0.6383296847343445},{"id":"https://openalex.org/keywords/decision-support-system","display_name":"Decision support system","score":0.4841621518135071},{"id":"https://openalex.org/keywords/data-science","display_name":"Data science","score":0.35795626044273376},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.2520940601825714}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6383296847343445},{"id":"https://openalex.org/C107327155","wikidata":"https://www.wikidata.org/wiki/Q330268","display_name":"Decision support system","level":2,"score":0.4841621518135071},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.35795626044273376},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.2520940601825714}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/aipr60534.2023.10440689","is_oa":false,"landing_page_url":"https://doi.org/10.1109/aipr60534.2023.10440689","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 IEEE Applied Imagery Pattern Recognition Workshop (AIPR)","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":0.4699999988079071}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":27,"referenced_works":["https://openalex.org/W1901129140","https://openalex.org/W2609077090","https://openalex.org/W3066358522","https://openalex.org/W3088698272","https://openalex.org/W3116043048","https://openalex.org/W3120071807","https://openalex.org/W3183988814","https://openalex.org/W4200100850","https://openalex.org/W4206337041","https://openalex.org/W4211177547","https://openalex.org/W4212811578","https://openalex.org/W4214502996","https://openalex.org/W4225411406","https://openalex.org/W4226063275","https://openalex.org/W4285176089","https://openalex.org/W4285802464","https://openalex.org/W4286639697","https://openalex.org/W4288083516","https://openalex.org/W4294796891","https://openalex.org/W4327713864","https://openalex.org/W4379745223","https://openalex.org/W4386275863","https://openalex.org/W4386308051","https://openalex.org/W4386327668","https://openalex.org/W4387088394","https://openalex.org/W6737170303","https://openalex.org/W6997060461"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2899084033","https://openalex.org/W2748952813","https://openalex.org/W2390279801","https://openalex.org/W4391913857","https://openalex.org/W2358668433","https://openalex.org/W4396701345","https://openalex.org/W2376932109","https://openalex.org/W2001405890","https://openalex.org/W4396696052"],"abstract_inverted_index":{"Computer":[0],"vision":[1],"has":[2],"the":[3,23,78,97,155,216,229],"potential":[4],"to":[5,106,153,161,167,209,242,248,274],"accelerate":[6],"decision":[7,26],"support":[8,27],"in":[9,115,122,145,223],"a":[10,16,40,104,146],"variety":[11],"of":[12,18,25,63,96,130,139,157,218,225],"medical":[13,31,59,127],"applications,":[14],"but":[15],"paucity":[17],"high-quality,":[19],"open-source":[20],"datasets":[21,230],"hinders":[22],"development":[24],"applications":[28,62,166],"for":[29,42,120,125,150,197,235,255,271],"open":[30,126],"environments":[32,51,264],"(i.e.,":[33],"non-laparoscopic).":[34],"Synthetic":[35,185],"data":[36,65,81,86,160,186,190,196,208,212,222,238,250],"holds":[37],"promise":[38,234],"as":[39,46,68,239,259,267,269],"solution":[41],"difficult-to-obtain":[43],"data,":[44],"such":[45,67,258],"images":[47,77,110,134,138],"from":[48,111],"high":[49],"stress":[50],"or":[52,169,214],"complicated":[53],"by":[54],"privacy":[55],"concerns":[56],"associated":[57],"with":[58,172,194,199,252],"imagery.":[60],"Modern":[61],"synthetic":[64,85,133,159,195,207,237],"generation":[66],"digital":[69,112],"twins":[70],"(DT)":[71],"can":[72],"create":[73],"high-fidelity":[74],"and":[75,90,99,118,135,246,262,265],"photo-realistic":[76],"surpass":[79],"traditional":[80],"augmentation":[82],"practices.":[83],"Moreover,":[84],"is":[87],"cost-effective,":[88],"efficient,":[89],"highly":[91],"scalable":[92],"after":[93],"initial":[94],"creation":[95],"assets":[98,114,266],"environment.":[100],"This":[101],"study":[102],"presents":[103],"framework":[105],"synthetically":[107],"generate":[108],"annotated":[109,132],"3-D":[113],"random":[116],"perspectives":[117],"orientations":[119],"use":[121],"computer-vision":[123],"(CV)":[124],"applications.":[128],"Datasets":[129],"1,000":[131],"681":[136],"real-world":[137,173,200,211,221],"six":[140,226],"object":[141],"classes":[142,227],"were":[143],"employed":[144],"transfer":[147],"learning":[148],"toolkit":[149],"an":[151,240],"experiment":[152,176],"determine":[154],"feasibility":[156],"utilizing":[158,236],"train":[162],"models":[163],"on":[164,181,206,220],"CV":[165],"augment":[168],"replace":[170],"training":[171,205,219],"data.":[174,201],"The":[175],"tested":[177],"model":[178,276],"performance":[179,217],"based":[180],"three":[182],"datasets:":[183],"1.":[184],"only;":[187,191],"2.":[188],"Real-world":[189],"3.":[192],"Training":[193],"evaluation":[198],"Results":[202,232],"showed":[203],"that":[204],"evaluate":[210],"met":[213],"exceeded":[215],"four":[224],"within":[228],"utilized.":[231],"show":[233],"alternative":[241],"costly,":[243],"time":[244],"consuming,":[245],"difficult":[247],"obtain":[249],"types":[251],"many":[253],"areas":[254],"further":[256],"study,":[257],"more":[260],"detailed":[261],"comprehensive":[263],"well":[268],"methodology":[270],"noise":[272],"injection":[273],"improve":[275],"performance.":[277]},"counts_by_year":[{"year":2025,"cited_by_count":3}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}
