{"id":"https://openalex.org/W3131362130","doi":"https://doi.org/10.1109/tmi.2021.3060551","title":"Interactive Few-Shot Learning: Limited Supervision, Better Medical Image Segmentation","display_name":"Interactive Few-Shot Learning: Limited Supervision, Better Medical Image Segmentation","publication_year":2021,"publication_date":"2021-02-19","ids":{"openalex":"https://openalex.org/W3131362130","doi":"https://doi.org/10.1109/tmi.2021.3060551","mag":"3131362130","pmid":"https://pubmed.ncbi.nlm.nih.gov/33606628"},"language":"en","primary_location":{"id":"doi:10.1109/tmi.2021.3060551","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tmi.2021.3060551","pdf_url":null,"source":{"id":"https://openalex.org/S58069681","display_name":"IEEE Transactions on Medical Imaging","issn_l":"0278-0062","issn":["0278-0062","1558-254X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Medical Imaging","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","pubmed"],"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/A5003036972","display_name":"Ruiwei Feng","orcid":"https://orcid.org/0000-0003-3732-7595"},"institutions":[{"id":"https://openalex.org/I168879160","display_name":"Zhejiang University of Science and Technology","ror":"https://ror.org/05mx0wr29","country_code":"CN","type":"education","lineage":["https://openalex.org/I168879160"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Ruiwei Feng","raw_affiliation_strings":["College of Computer Science and Technology, Zhejiang University, Hangzhou, China"],"raw_orcid":"https://orcid.org/0000-0003-3732-7595","affiliations":[{"raw_affiliation_string":"College of Computer Science and Technology, Zhejiang University, Hangzhou, China","institution_ids":["https://openalex.org/I168879160"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100553726","display_name":"Xiangshang Zheng","orcid":null},"institutions":[{"id":"https://openalex.org/I168879160","display_name":"Zhejiang University of Science and Technology","ror":"https://ror.org/05mx0wr29","country_code":"CN","type":"education","lineage":["https://openalex.org/I168879160"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiangshang Zheng","raw_affiliation_strings":["College of Computer Science and Technology, Zhejiang University, Hangzhou, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Computer Science and Technology, Zhejiang University, Hangzhou, China","institution_ids":["https://openalex.org/I168879160"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5008695351","display_name":"Tianxiang Gao","orcid":"https://orcid.org/0000-0001-8797-4147"},"institutions":[{"id":"https://openalex.org/I168879160","display_name":"Zhejiang University of Science and Technology","ror":"https://ror.org/05mx0wr29","country_code":"CN","type":"education","lineage":["https://openalex.org/I168879160"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Tianxiang Gao","raw_affiliation_strings":["College of Computer Science and Technology, Zhejiang University, Hangzhou, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Computer Science and Technology, Zhejiang University, Hangzhou, China","institution_ids":["https://openalex.org/I168879160"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5023258354","display_name":"Jintai Chen","orcid":"https://orcid.org/0000-0002-3199-2597"},"institutions":[{"id":"https://openalex.org/I168879160","display_name":"Zhejiang University of Science and Technology","ror":"https://ror.org/05mx0wr29","country_code":"CN","type":"education","lineage":["https://openalex.org/I168879160"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jintai Chen","raw_affiliation_strings":["College of Computer Science and Technology, Zhejiang University, Hangzhou, China"],"raw_orcid":"https://orcid.org/0000-0002-3199-2597","affiliations":[{"raw_affiliation_string":"College of Computer Science and Technology, Zhejiang University, Hangzhou, China","institution_ids":["https://openalex.org/I168879160"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5000731827","display_name":"Wenzhe Wang","orcid":"https://orcid.org/0000-0001-7431-9039"},"institutions":[{"id":"https://openalex.org/I168879160","display_name":"Zhejiang University of Science and Technology","ror":"https://ror.org/05mx0wr29","country_code":"CN","type":"education","lineage":["https://openalex.org/I168879160"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wenzhe Wang","raw_affiliation_strings":["College of Computer Science and Technology, Zhejiang University, Hangzhou, China"],"raw_orcid":"https://orcid.org/0000-0001-7431-9039","affiliations":[{"raw_affiliation_string":"College of Computer Science and Technology, Zhejiang University, Hangzhou, China","institution_ids":["https://openalex.org/I168879160"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5060901632","display_name":"Danny Z. Chen","orcid":"https://orcid.org/0000-0001-6565-2884"},"institutions":[{"id":"https://openalex.org/I107639228","display_name":"University of Notre Dame","ror":"https://ror.org/00mkhxb43","country_code":"US","type":"education","lineage":["https://openalex.org/I107639228"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Danny Z. Chen","raw_affiliation_strings":["Department of Computer Science and Engineering, University of Notre Dame, Notre Dame, IN, USA"],"raw_orcid":"https://orcid.org/0000-0001-6565-2884","affiliations":[{"raw_affiliation_string":"Department of Computer Science and Engineering, University of Notre Dame, Notre Dame, IN, USA","institution_ids":["https://openalex.org/I107639228"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5071068569","display_name":"Jian Wu","orcid":"https://orcid.org/0000-0002-3230-6392"},"institutions":[{"id":"https://openalex.org/I168879160","display_name":"Zhejiang University of Science and Technology","ror":"https://ror.org/05mx0wr29","country_code":"CN","type":"education","lineage":["https://openalex.org/I168879160"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jian Wu","raw_affiliation_strings":["College of Computer Science and Technology, Zhejiang University, Hangzhou, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Computer Science and Technology, Zhejiang University, Hangzhou, China","institution_ids":["https://openalex.org/I168879160"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":7,"corresponding_author_ids":["https://openalex.org/A5003036972"],"corresponding_institution_ids":["https://openalex.org/I168879160"],"apc_list":null,"apc_paid":null,"fwci":11.7583,"has_fulltext":false,"cited_by_count":129,"citation_normalized_percentile":{"value":0.99120049,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":100},"biblio":{"volume":"40","issue":"10","first_page":"2575","last_page":"2588"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11775","display_name":"COVID-19 diagnosis using AI","score":0.9987999796867371,"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"}},"topics":[{"id":"https://openalex.org/T11775","display_name":"COVID-19 diagnosis using AI","score":0.9987999796867371,"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.9976999759674072,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/T12422","display_name":"Radiomics and Machine Learning in Medical Imaging","score":0.9976000189781189,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.8216992616653442},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7993152141571045},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7240957021713257},{"id":"https://openalex.org/keywords/shot","display_name":"Shot (pellet)","score":0.651964008808136},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.5936861038208008},{"id":"https://openalex.org/keywords/scale-space-segmentation","display_name":"Scale-space segmentation","score":0.5434288382530212},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.5291814208030701},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5064016580581665},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4931151568889618},{"id":"https://openalex.org/keywords/annotation","display_name":"Annotation","score":0.4887826144695282},{"id":"https://openalex.org/keywords/metric","display_name":"Metric (unit)","score":0.46032634377479553},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3561660349369049}],"concepts":[{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.8216992616653442},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7993152141571045},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7240957021713257},{"id":"https://openalex.org/C2778344882","wikidata":"https://www.wikidata.org/wiki/Q278938","display_name":"Shot (pellet)","level":2,"score":0.651964008808136},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.5936861038208008},{"id":"https://openalex.org/C65885262","wikidata":"https://www.wikidata.org/wiki/Q7429708","display_name":"Scale-space segmentation","level":4,"score":0.5434288382530212},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.5291814208030701},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5064016580581665},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4931151568889618},{"id":"https://openalex.org/C2776321320","wikidata":"https://www.wikidata.org/wiki/Q857525","display_name":"Annotation","level":2,"score":0.4887826144695282},{"id":"https://openalex.org/C176217482","wikidata":"https://www.wikidata.org/wiki/Q860554","display_name":"Metric (unit)","level":2,"score":0.46032634377479553},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3561660349369049},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C178790620","wikidata":"https://www.wikidata.org/wiki/Q11351","display_name":"Organic chemistry","level":1,"score":0.0},{"id":"https://openalex.org/C187736073","wikidata":"https://www.wikidata.org/wiki/Q2920921","display_name":"Management","level":1,"score":0.0},{"id":"https://openalex.org/C21547014","wikidata":"https://www.wikidata.org/wiki/Q1423657","display_name":"Operations management","level":1,"score":0.0}],"mesh":[{"descriptor_ui":"D000066908","descriptor_name":"Simulation Training","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D000066908","descriptor_name":"Simulation Training","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D000066908","descriptor_name":"Simulation Training","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D000077321","descriptor_name":"Deep Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D000077321","descriptor_name":"Deep Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D000077321","descriptor_name":"Deep Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D000465","descriptor_name":"Algorithms","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000465","descriptor_name":"Algorithms","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000465","descriptor_name":"Algorithms","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false}],"locations_count":2,"locations":[{"id":"doi:10.1109/tmi.2021.3060551","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tmi.2021.3060551","pdf_url":null,"source":{"id":"https://openalex.org/S58069681","display_name":"IEEE Transactions on Medical Imaging","issn_l":"0278-0062","issn":["0278-0062","1558-254X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Medical Imaging","raw_type":"journal-article"},{"id":"pmid:33606628","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/33606628","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE transactions on medical imaging","raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G2783630996","display_name":null,"funder_award_id":"K17-518051-02","funder_id":"https://openalex.org/F4320322927","funder_display_name":"Zhejiang University"},{"id":"https://openalex.org/G4037434717","display_name":null,"funder_award_id":"K18-511120-004","funder_id":"https://openalex.org/F4320322927","funder_display_name":"Zhejiang University"},{"id":"https://openalex.org/G4965254154","display_name":null,"funder_award_id":"K17-511120-017","funder_id":"https://openalex.org/F4320322927","funder_display_name":"Zhejiang University"},{"id":"https://openalex.org/G511542782","display_name":null,"funder_award_id":"2019KY667","funder_id":"https://openalex.org/F4320336309","funder_display_name":"Medical and Health Research Project of Zhejiang Province"},{"id":"https://openalex.org/G7626749479","display_name":null,"funder_award_id":"CCF-1617735","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G8327927261","display_name":null,"funder_award_id":"61672453","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"},{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320322927","display_name":"Zhejiang University","ror":"https://ror.org/00a2xv884"},{"id":"https://openalex.org/F4320336309","display_name":"Medical and Health Research Project of Zhejiang Province","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":89,"referenced_works":["https://openalex.org/W1686810756","https://openalex.org/W1901129140","https://openalex.org/W2115733720","https://openalex.org/W2117539524","https://openalex.org/W2175082661","https://openalex.org/W2188119724","https://openalex.org/W2253429366","https://openalex.org/W2288892845","https://openalex.org/W2300469113","https://openalex.org/W2345010043","https://openalex.org/W2346062110","https://openalex.org/W2464708700","https://openalex.org/W2527062305","https://openalex.org/W2613456556","https://openalex.org/W2625559849","https://openalex.org/W2728648333","https://openalex.org/W2732931556","https://openalex.org/W2736597453","https://openalex.org/W2750023899","https://openalex.org/W2750925197","https://openalex.org/W2751665805","https://openalex.org/W2754560798","https://openalex.org/W2763160469","https://openalex.org/W2766530444","https://openalex.org/W2798976889","https://openalex.org/W2803677800","https://openalex.org/W2805494874","https://openalex.org/W2808912095","https://openalex.org/W2811240690","https://openalex.org/W2883245728","https://openalex.org/W2884065486","https://openalex.org/W2886049744","https://openalex.org/W2886773299","https://openalex.org/W2891451067","https://openalex.org/W2891798045","https://openalex.org/W2893918048","https://openalex.org/W2902683551","https://openalex.org/W2903655137","https://openalex.org/W2910094941","https://openalex.org/W2911066482","https://openalex.org/W2921110842","https://openalex.org/W2933796343","https://openalex.org/W2944580495","https://openalex.org/W2959874569","https://openalex.org/W2962835968","https://openalex.org/W2962858109","https://openalex.org/W2963078159","https://openalex.org/W2963588172","https://openalex.org/W2964028171","https://openalex.org/W2964150021","https://openalex.org/W2964250774","https://openalex.org/W2964317695","https://openalex.org/W2964890799","https://openalex.org/W2970546341","https://openalex.org/W2971013993","https://openalex.org/W2974231122","https://openalex.org/W2979808779","https://openalex.org/W2980081640","https://openalex.org/W2982456085","https://openalex.org/W2990230185","https://openalex.org/W3005933814","https://openalex.org/W3014795415","https://openalex.org/W3026420023","https://openalex.org/W3033502887","https://openalex.org/W3034942609","https://openalex.org/W3085364681","https://openalex.org/W3089740767","https://openalex.org/W3101310341","https://openalex.org/W3104368407","https://openalex.org/W4309233581","https://openalex.org/W6637373629","https://openalex.org/W6639824700","https://openalex.org/W6685104986","https://openalex.org/W6687029160","https://openalex.org/W6743360694","https://openalex.org/W6743689066","https://openalex.org/W6744114936","https://openalex.org/W6752846148","https://openalex.org/W6754568377","https://openalex.org/W6755301897","https://openalex.org/W6756657096","https://openalex.org/W6758047254","https://openalex.org/W6761292208","https://openalex.org/W6762133282","https://openalex.org/W6765789609","https://openalex.org/W6766621745","https://openalex.org/W6768160236","https://openalex.org/W6774615226","https://openalex.org/W6777835625"],"related_works":["https://openalex.org/W2185902295","https://openalex.org/W2103507220","https://openalex.org/W3144569342","https://openalex.org/W2945274617","https://openalex.org/W4313052709","https://openalex.org/W4205800335","https://openalex.org/W2055202857","https://openalex.org/W2022929107","https://openalex.org/W80586315","https://openalex.org/W2758994127"],"abstract_inverted_index":{"Many":[0],"known":[1,83],"supervised":[2],"deep":[3],"learning":[4,45,49],"methods":[5,23,32,195],"for":[6,17,143,215],"medical":[7,71],"image":[8,72],"segmentation":[9,22,56,73,85,93,118,164,185,218],"suffer":[10],"an":[11,128,148,176],"expensive":[12],"burden":[13,69],"of":[14,70,81,119],"data":[15],"annotation":[16,68],"model":[18],"training.":[19],"Recently,":[20],"few-shot":[21,48,55,84,92,163,184,217],"were":[24],"proposed":[25],"to":[26,37,115,136,161,166],"alleviate":[27],"this":[28],"burden,":[29],"but":[30,75],"such":[31],"often":[33],"showed":[34],"poor":[35],"adaptability":[36],"the":[38,47,67,78,82,117,141,144,159,172,193,201,205,216],"target":[39,145,173],"tasks.":[40],"By":[41],"prudently":[42],"introducing":[43],"interactive":[44,149,177,206],"into":[46],"strategy,":[50],"we":[51,88,126],"develop":[52],"a":[53,90,105],"novel":[54],"approach":[57,157,191],"called":[58,95],"Interactive":[59,129],"Few-shot":[60,98],"Learning":[61,99],"(IFSL),":[62],"which":[63,102],"not":[64],"only":[65,104],"addresses":[66],"models":[74,165],"also":[76],"tackles":[77],"common":[79],"issues":[80],"methods.":[86],"First,":[87],"design":[89],"new":[91],"structure,":[94],"Medical":[96],"Prior-based":[97],"Network":[100],"(MPrNet),":[101],"uses":[103],"few":[106],"annotated":[107],"samples":[108],"(e.g.,":[109],"10":[110],"samples)":[111],"as":[112],"support":[113],"images":[114,121],"guide":[116],"query":[120],"without":[122],"any":[123],"pre-training.":[124],"Then,":[125],"propose":[127],"Learning-based":[130],"Test":[131],"Time":[132],"Optimization":[133],"Algorithm":[134],"(IL-TTOA)":[135,209],"strengthen":[137],"our":[138,152,155,189],"MPrNet":[139],"on":[140,171,182],"fly":[142],"task":[146],"in":[147,175,200],"fashion.":[150],"To":[151],"best":[153],"knowledge,":[154],"IFSL":[156,190],"is":[158],"first":[160],"allow":[162],"be":[167],"optimized":[168],"and":[169,178],"strengthened":[170],"tasks":[174,186],"controllable":[179],"manner.":[180],"Experiments":[181],"four":[183],"show":[187],"that":[188],"outperforms":[192],"state-of-the-art":[194],"by":[196],"more":[197],"than":[198],"20%":[199],"DSC":[202,213],"metric.":[203],"Specifically,":[204],"optimization":[207],"algorithm":[208],"further":[210],"contributes":[211],"~10%":[212],"improvement":[214],"models.":[219]},"counts_by_year":[{"year":2026,"cited_by_count":10},{"year":2025,"cited_by_count":37},{"year":2024,"cited_by_count":36},{"year":2023,"cited_by_count":30},{"year":2022,"cited_by_count":14},{"year":2021,"cited_by_count":2}],"updated_date":"2026-05-07T13:39:58.223016","created_date":"2025-10-10T00:00:00"}