{"id":"https://openalex.org/W4387346437","doi":"https://doi.org/10.1145/3584371.3612980","title":"Choice Over Effort: Mapping and Diagnosing Augmented Whole Slide Image Datasets with Training Dynamics","display_name":"Choice Over Effort: Mapping and Diagnosing Augmented Whole Slide Image Datasets with Training Dynamics","publication_year":2023,"publication_date":"2023-09-03","ids":{"openalex":"https://openalex.org/W4387346437","doi":"https://doi.org/10.1145/3584371.3612980"},"language":"en","primary_location":{"id":"doi:10.1145/3584371.3612980","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3584371.3612980","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3584371.3612980","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 14th ACM International Conference on Bioinformatics, Computational Biology, and Health Informatics","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://dl.acm.org/doi/pdf/10.1145/3584371.3612980","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5034193264","display_name":"Wenqi Shi","orcid":"https://orcid.org/0000-0001-8972-7342"},"institutions":[{"id":"https://openalex.org/I130701444","display_name":"Georgia Institute of Technology","ror":"https://ror.org/01zkghx44","country_code":"US","type":"education","lineage":["https://openalex.org/I130701444"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Wenqi Shi","raw_affiliation_strings":["Georgia Institute of Technology, Atlanta, USA"],"raw_orcid":"https://orcid.org/0000-0001-8972-7342","affiliations":[{"raw_affiliation_string":"Georgia Institute of Technology, Atlanta, USA","institution_ids":["https://openalex.org/I130701444"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5089017848","display_name":"Benoit Marteau","orcid":"https://orcid.org/0000-0002-4177-7161"},"institutions":[{"id":"https://openalex.org/I130701444","display_name":"Georgia Institute of Technology","ror":"https://ror.org/01zkghx44","country_code":"US","type":"education","lineage":["https://openalex.org/I130701444"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Benoit Louis Marteau","raw_affiliation_strings":["Georgia Institute of Technology, Atlanta, USA"],"raw_orcid":"https://orcid.org/0000-0002-4177-7161","affiliations":[{"raw_affiliation_string":"Georgia Institute of Technology, Atlanta, USA","institution_ids":["https://openalex.org/I130701444"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5057134532","display_name":"Felipe Giuste","orcid":"https://orcid.org/0000-0002-8355-3705"},"institutions":[{"id":"https://openalex.org/I130701444","display_name":"Georgia Institute of Technology","ror":"https://ror.org/01zkghx44","country_code":"US","type":"education","lineage":["https://openalex.org/I130701444"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Felipe Giuste","raw_affiliation_strings":["Georgia Institute of Technology, Atlanta, USA"],"raw_orcid":"https://orcid.org/0000-0002-8355-3705","affiliations":[{"raw_affiliation_string":"Georgia Institute of Technology, Atlanta, USA","institution_ids":["https://openalex.org/I130701444"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5030096887","display_name":"May D. Wang","orcid":"https://orcid.org/0000-0003-3961-3608"},"institutions":[{"id":"https://openalex.org/I130701444","display_name":"Georgia Institute of Technology","ror":"https://ror.org/01zkghx44","country_code":"US","type":"education","lineage":["https://openalex.org/I130701444"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"May Dongmei Wang","raw_affiliation_strings":["Georgia Institute of Technology, Atlanta, USA"],"raw_orcid":"https://orcid.org/0000-0003-3961-3608","affiliations":[{"raw_affiliation_string":"Georgia Institute of Technology, Atlanta, USA","institution_ids":["https://openalex.org/I130701444"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5034193264"],"corresponding_institution_ids":["https://openalex.org/I130701444"],"apc_list":null,"apc_paid":null,"fwci":0.9256,"has_fulltext":true,"cited_by_count":3,"citation_normalized_percentile":{"value":0.76226826,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11189","display_name":"Transplantation: Methods and Outcomes","score":0.9993000030517578,"subfield":{"id":"https://openalex.org/subfields/2746","display_name":"Surgery"},"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/T11189","display_name":"Transplantation: Methods and Outcomes","score":0.9993000030517578,"subfield":{"id":"https://openalex.org/subfields/2746","display_name":"Surgery"},"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/T11775","display_name":"COVID-19 diagnosis using AI","score":0.9847999811172485,"subfield":{"id":"https://openalex.org/subfields/2741","display_name":"Radiology, Nuclear Medicine and Imaging"},"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/T11660","display_name":"Blood groups and transfusion","score":0.9696999788284302,"subfield":{"id":"https://openalex.org/subfields/2720","display_name":"Hematology"},"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":0.7886569499969482},{"id":"https://openalex.org/keywords/scalability","display_name":"Scalability","score":0.6711477637290955},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5180032849311829},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4648508131504059},{"id":"https://openalex.org/keywords/database","display_name":"Database","score":0.12316977977752686}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7886569499969482},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.6711477637290955},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5180032849311829},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4648508131504059},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.12316977977752686}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3584371.3612980","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3584371.3612980","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3584371.3612980","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 14th ACM International Conference on Bioinformatics, Computational Biology, and Health Informatics","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.1145/3584371.3612980","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3584371.3612980","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3584371.3612980","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 14th ACM International Conference on Bioinformatics, Computational Biology, and Health Informatics","raw_type":"proceedings-article"},"sustainable_development_goals":[{"display_name":"Good health and well-being","id":"https://metadata.un.org/sdg/3","score":0.5600000023841858}],"awards":[{"id":"https://openalex.org/G3547598651","display_name":null,"funder_award_id":"5R01HL119747","funder_id":"https://openalex.org/F4320332161","funder_display_name":"National Institutes of Health"},{"id":"https://openalex.org/G5208267828","display_name":null,"funder_award_id":"1651360","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"}],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"},{"id":"https://openalex.org/F4320313524","display_name":"Children's Healthcare of Atlanta","ror":"https://ror.org/050fhx250"},{"id":"https://openalex.org/F4320332161","display_name":"National Institutes of Health","ror":"https://ror.org/01cwqze88"},{"id":"https://openalex.org/F4320332656","display_name":"Parker H. Petit Institute for Bioengineering and Bioscience","ror":"https://ror.org/01zkghx44"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4387346437.pdf","grobid_xml":"https://content.openalex.org/works/W4387346437.grobid-xml"},"referenced_works_count":20,"referenced_works":["https://openalex.org/W2041566765","https://openalex.org/W2265288362","https://openalex.org/W2292493149","https://openalex.org/W2796573343","https://openalex.org/W2954490207","https://openalex.org/W2956378751","https://openalex.org/W2990099053","https://openalex.org/W3036167779","https://openalex.org/W3096831136","https://openalex.org/W3103649165","https://openalex.org/W3137757395","https://openalex.org/W3189709464","https://openalex.org/W4221086349","https://openalex.org/W4283753137","https://openalex.org/W4287121833","https://openalex.org/W4319003560","https://openalex.org/W4323044448","https://openalex.org/W6638984823","https://openalex.org/W6779823529","https://openalex.org/W6796588791"],"related_works":["https://openalex.org/W2961085424","https://openalex.org/W4306674287","https://openalex.org/W3046775127","https://openalex.org/W3107602296","https://openalex.org/W4394896187","https://openalex.org/W3170094116","https://openalex.org/W4386462264","https://openalex.org/W4364306694","https://openalex.org/W4312192474","https://openalex.org/W4283697347"],"abstract_inverted_index":{"In":[0],"pediatric":[1,67],"heart":[2,59],"transplantation,":[3],"manual":[4,32],"annotations":[5,33],"with":[6,76],"interob-server":[7],"and":[8,49,79,84,103,114],"intraobserver":[9],"variability":[10],"among":[11],"cardiovascular":[12],"pathology":[13,28],"experts":[14],"lead":[15],"to":[16,82,126],"significant":[17],"disagreements":[18],"about":[19],"the":[20,86,90,109,132],"severity":[21],"of":[22,34,66,111,134],"rejection.":[23],"Artificial":[24],"intelligence":[25],"(AI)-enabled":[26],"computational":[27],"usually":[29],"requires":[30],"large-scale":[31],"gigapixel":[35],"whole-slide":[36,64],"images":[37,65],"(WSIs)":[38],"for":[39,57],"effective":[40],"model":[41,91,97],"training.":[42,98],"To":[43],"address":[44],"these":[45],"challenges,":[46],"we":[47,70],"develop":[48],"validate":[50],"an":[51],"AI-enabled":[52],"rare":[53,128],"disease":[54,129],"detection":[55,62,130],"framework":[56,121],"automating":[58],"transplant":[60],"rejection":[61],"from":[63],"patients.":[68],"Specifically,":[69],"conduct":[71],"a":[72],"novel":[73],"dataset":[74],"cartography":[75],"data":[77],"maps":[78],"training":[80],"dynamics":[81],"map":[83],"diagnose":[85],"augmented":[87],"samples,":[88],"exploring":[89],"behavior":[92],"on":[93,101],"individual":[94],"instances":[95],"during":[96],"Extensive":[99],"experiments":[100],"internal":[102],"external":[104],"patient":[105],"cohorts":[106],"have":[107],"demonstrated":[108],"feasibility":[110],"both":[112],"tile-level":[113],"biopsy-level":[115],"detection.":[116],"The":[117],"proposed":[118],"data-efficient":[119],"learning":[120],"may":[122],"support":[123],"seamless":[124],"scalability":[125],"real-world":[127],"without":[131],"burden":[133],"iterative":[135],"expert":[136],"annotations.":[137]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2023,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
