{"id":"https://openalex.org/W4362694317","doi":"https://doi.org/10.1117/12.2655266","title":"Spatially aware transformer networks for contextual prediction of diabetic nephropathy progression from whole slide images","display_name":"Spatially aware transformer networks for contextual prediction of diabetic nephropathy progression from whole slide images","publication_year":2023,"publication_date":"2023-04-07","ids":{"openalex":"https://openalex.org/W4362694317","doi":"https://doi.org/10.1117/12.2655266","pmid":"https://pubmed.ncbi.nlm.nih.gov/37818350"},"language":"en","primary_location":{"id":"doi:10.1117/12.2655266","is_oa":false,"landing_page_url":"https://doi.org/10.1117/12.2655266","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Medical Imaging 2023: Digital and Computational Pathology","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref","pubmed"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://pmc.ncbi.nlm.nih.gov/articles/PMC10563813/pdf/nihms-1935804.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5019504069","display_name":"Benjamin Shickel","orcid":"https://orcid.org/0000-0002-5304-7027"},"institutions":[{"id":"https://openalex.org/I33213144","display_name":"University of Florida","ror":"https://ror.org/02y3ad647","country_code":"US","type":"education","lineage":["https://openalex.org/I33213144"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Benjamin Shickel","raw_affiliation_strings":["Dept. of Medicine, University of Florida, Gainesville, FL, USA","Univ. of Florida Intelligent Critical Care Center, Gainesville, FL, USA","Univ. of Florida (United States)"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Dept. of Medicine, University of Florida, Gainesville, FL, USA","institution_ids":["https://openalex.org/I33213144"]},{"raw_affiliation_string":"Univ. of Florida Intelligent Critical Care Center, Gainesville, FL, USA","institution_ids":["https://openalex.org/I33213144"]},{"raw_affiliation_string":"Univ. of Florida (United States)","institution_ids":["https://openalex.org/I33213144"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5082308621","display_name":"Nicholas Lucarelli","orcid":"https://orcid.org/0000-0002-5454-7074"},"institutions":[{"id":"https://openalex.org/I33213144","display_name":"University of Florida","ror":"https://ror.org/02y3ad647","country_code":"US","type":"education","lineage":["https://openalex.org/I33213144"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Nicholas Lucarelli","raw_affiliation_strings":["Dept. of Biomedical Engineering, Univ. of Florida, Gainesville, FL, USA","Univ. of Florida (United States)"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Dept. of Biomedical Engineering, Univ. of Florida, Gainesville, FL, USA","institution_ids":["https://openalex.org/I33213144"]},{"raw_affiliation_string":"Univ. of Florida (United States)","institution_ids":["https://openalex.org/I33213144"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5070174982","display_name":"Adish S. Rao","orcid":null},"institutions":[{"id":"https://openalex.org/I33213144","display_name":"University of Florida","ror":"https://ror.org/02y3ad647","country_code":"US","type":"education","lineage":["https://openalex.org/I33213144"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Adish Rao","raw_affiliation_strings":["Dept. of Computer and Information Science and Engineering, Univ. of Florida, Gainesville, FL","Univ. of Florida (United States)"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Dept. of Computer and Information Science and Engineering, Univ. of Florida, Gainesville, FL","institution_ids":["https://openalex.org/I33213144"]},{"raw_affiliation_string":"Univ. of Florida (United States)","institution_ids":["https://openalex.org/I33213144"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5013384481","display_name":"Donghwan Yun","orcid":"https://orcid.org/0000-0001-6566-5183"},"institutions":[{"id":"https://openalex.org/I139264467","display_name":"Seoul National University","ror":"https://ror.org/04h9pn542","country_code":"KR","type":"education","lineage":["https://openalex.org/I139264467"]},{"id":"https://openalex.org/I2802457231","display_name":"New Generation University College","ror":"https://ror.org/015aem925","country_code":"ET","type":"education","lineage":["https://openalex.org/I2802457231"]}],"countries":["ET","KR"],"is_corresponding":false,"raw_author_name":"Donghwan Yun","raw_affiliation_strings":["Dept. of Internal Medicine, Seoul National Univ. College of Medicine, Seoul, Korea","Seoul National Univ. (Korea, Republic of)"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Dept. of Internal Medicine, Seoul National Univ. College of Medicine, Seoul, Korea","institution_ids":["https://openalex.org/I2802457231"]},{"raw_affiliation_string":"Seoul National Univ. (Korea, Republic of)","institution_ids":["https://openalex.org/I139264467"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5020847797","display_name":"Kyung Chul Moon","orcid":"https://orcid.org/0000-0002-1969-8360"},"institutions":[{"id":"https://openalex.org/I139264467","display_name":"Seoul National University","ror":"https://ror.org/04h9pn542","country_code":"KR","type":"education","lineage":["https://openalex.org/I139264467"]},{"id":"https://openalex.org/I2802457231","display_name":"New Generation University College","ror":"https://ror.org/015aem925","country_code":"ET","type":"education","lineage":["https://openalex.org/I2802457231"]}],"countries":["ET","KR"],"is_corresponding":false,"raw_author_name":"Kyung Chul Moon","raw_affiliation_strings":["Dept. of Internal Medicine, Seoul National Univ. College of Medicine, Seoul, Korea","Seoul National Univ. (Korea, Republic of)"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Dept. of Internal Medicine, Seoul National Univ. College of Medicine, Seoul, Korea","institution_ids":["https://openalex.org/I2802457231"]},{"raw_affiliation_string":"Seoul National Univ. (Korea, Republic of)","institution_ids":["https://openalex.org/I139264467"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5031939393","display_name":"Han Seung Seok","orcid":null},"institutions":[{"id":"https://openalex.org/I139264467","display_name":"Seoul National University","ror":"https://ror.org/04h9pn542","country_code":"KR","type":"education","lineage":["https://openalex.org/I139264467"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Han Seung Seok","raw_affiliation_strings":["Seoul National Univ. (Korea, Republic of)"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Seoul National Univ. (Korea, Republic of)","institution_ids":["https://openalex.org/I139264467"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5044061952","display_name":"Pinaki Sarder","orcid":"https://orcid.org/0000-0003-2450-5233"},"institutions":[{"id":"https://openalex.org/I33213144","display_name":"University of Florida","ror":"https://ror.org/02y3ad647","country_code":"US","type":"education","lineage":["https://openalex.org/I33213144"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Pinaki Sarder","raw_affiliation_strings":["Dept. of Medicine, University of Florida, Gainesville, FL, USA","Univ. of Florida Intelligent Critical Care Center, Gainesville, FL, USA","Univ. of Florida (United States)"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Dept. of Medicine, University of Florida, Gainesville, FL, USA","institution_ids":["https://openalex.org/I33213144"]},{"raw_affiliation_string":"Univ. of Florida Intelligent Critical Care Center, Gainesville, FL, USA","institution_ids":["https://openalex.org/I33213144"]},{"raw_affiliation_string":"Univ. of Florida (United States)","institution_ids":["https://openalex.org/I33213144"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.5118,"has_fulltext":true,"cited_by_count":3,"citation_normalized_percentile":{"value":0.82121212,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":96},"biblio":{"volume":"12471","issue":null,"first_page":"19","last_page":"19"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10552","display_name":"Colorectal Cancer Screening and Detection","score":0.9984999895095825,"subfield":{"id":"https://openalex.org/subfields/2730","display_name":"Oncology"},"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/T10552","display_name":"Colorectal Cancer Screening and Detection","score":0.9984999895095825,"subfield":{"id":"https://openalex.org/subfields/2730","display_name":"Oncology"},"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/T10862","display_name":"AI in cancer detection","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/T10052","display_name":"Medical Image Segmentation Techniques","score":0.9923999905586243,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/overfitting","display_name":"Overfitting","score":0.7295419573783875},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6892912983894348},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.649705171585083},{"id":"https://openalex.org/keywords/receiver-operating-characteristic","display_name":"Receiver operating characteristic","score":0.5781665444374084},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.5646119713783264},{"id":"https://openalex.org/keywords/autoencoder","display_name":"Autoencoder","score":0.5065094232559204},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4983506202697754},{"id":"https://openalex.org/keywords/random-forest","display_name":"Random forest","score":0.4911598861217499},{"id":"https://openalex.org/keywords/generalizability-theory","display_name":"Generalizability theory","score":0.4658900797367096},{"id":"https://openalex.org/keywords/diabetic-nephropathy","display_name":"Diabetic nephropathy","score":0.44489848613739014},{"id":"https://openalex.org/keywords/euclidean-distance","display_name":"Euclidean distance","score":0.42815470695495605},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3351980447769165},{"id":"https://openalex.org/keywords/medicine","display_name":"Medicine","score":0.3158056139945984},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.3094164729118347},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.2599934935569763},{"id":"https://openalex.org/keywords/internal-medicine","display_name":"Internal medicine","score":0.2103264331817627},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.201114684343338},{"id":"https://openalex.org/keywords/kidney","display_name":"Kidney","score":0.1533830463886261}],"concepts":[{"id":"https://openalex.org/C22019652","wikidata":"https://www.wikidata.org/wiki/Q331309","display_name":"Overfitting","level":3,"score":0.7295419573783875},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6892912983894348},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.649705171585083},{"id":"https://openalex.org/C58471807","wikidata":"https://www.wikidata.org/wiki/Q327120","display_name":"Receiver operating characteristic","level":2,"score":0.5781665444374084},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5646119713783264},{"id":"https://openalex.org/C101738243","wikidata":"https://www.wikidata.org/wiki/Q786435","display_name":"Autoencoder","level":3,"score":0.5065094232559204},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4983506202697754},{"id":"https://openalex.org/C169258074","wikidata":"https://www.wikidata.org/wiki/Q245748","display_name":"Random forest","level":2,"score":0.4911598861217499},{"id":"https://openalex.org/C27158222","wikidata":"https://www.wikidata.org/wiki/Q5532422","display_name":"Generalizability theory","level":2,"score":0.4658900797367096},{"id":"https://openalex.org/C2779922275","wikidata":"https://www.wikidata.org/wiki/Q1129105","display_name":"Diabetic nephropathy","level":3,"score":0.44489848613739014},{"id":"https://openalex.org/C120174047","wikidata":"https://www.wikidata.org/wiki/Q847073","display_name":"Euclidean distance","level":2,"score":0.42815470695495605},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3351980447769165},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.3158056139945984},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.3094164729118347},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.2599934935569763},{"id":"https://openalex.org/C126322002","wikidata":"https://www.wikidata.org/wiki/Q11180","display_name":"Internal medicine","level":1,"score":0.2103264331817627},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.201114684343338},{"id":"https://openalex.org/C2780091579","wikidata":"https://www.wikidata.org/wiki/Q9377","display_name":"Kidney","level":2,"score":0.1533830463886261}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1117/12.2655266","is_oa":false,"landing_page_url":"https://doi.org/10.1117/12.2655266","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Medical Imaging 2023: Digital and Computational Pathology","raw_type":"proceedings-article"},{"id":"pmid:37818350","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/37818350","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":"Proceedings of SPIE--the International Society for Optical Engineering","raw_type":null},{"id":"pmh:oai:pubmedcentral.nih.gov:10563813","is_oa":true,"landing_page_url":"https://www.ncbi.nlm.nih.gov/pmc/articles/10563813","pdf_url":"https://pmc.ncbi.nlm.nih.gov/articles/PMC10563813/pdf/nihms-1935804.pdf","source":{"id":"https://openalex.org/S2764455111","display_name":"PubMed Central","issn_l":null,"issn":null,"is_oa":true,"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":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Proc SPIE Int Soc Opt Eng","raw_type":"Text"}],"best_oa_location":{"id":"pmh:oai:pubmedcentral.nih.gov:10563813","is_oa":true,"landing_page_url":"https://www.ncbi.nlm.nih.gov/pmc/articles/10563813","pdf_url":"https://pmc.ncbi.nlm.nih.gov/articles/PMC10563813/pdf/nihms-1935804.pdf","source":{"id":"https://openalex.org/S2764455111","display_name":"PubMed Central","issn_l":null,"issn":null,"is_oa":true,"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":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Proc SPIE Int Soc Opt Eng","raw_type":"Text"},"sustainable_development_goals":[{"score":0.4099999964237213,"display_name":"Partnerships for the goals","id":"https://metadata.un.org/sdg/17"}],"awards":[{"id":"https://openalex.org/G2253811589","display_name":null,"funder_award_id":"R01 DK114485","funder_id":"https://openalex.org/F4320337357","funder_display_name":"National Institute of Diabetes and Digestive and Kidney Diseases"}],"funders":[{"id":"https://openalex.org/F4320337357","display_name":"National Institute of Diabetes and Digestive and Kidney Diseases","ror":"https://ror.org/00adh9b73"}],"has_content":{"grobid_xml":false,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4362694317.pdf"},"referenced_works_count":43,"referenced_works":["https://openalex.org/W1985941010","https://openalex.org/W2016121271","https://openalex.org/W2019605179","https://openalex.org/W2136490577","https://openalex.org/W2150780222","https://openalex.org/W2347118682","https://openalex.org/W2504150216","https://openalex.org/W2571156573","https://openalex.org/W2594748846","https://openalex.org/W2790284551","https://openalex.org/W2900423370","https://openalex.org/W2905062994","https://openalex.org/W2910268554","https://openalex.org/W2952003460","https://openalex.org/W2952833648","https://openalex.org/W2952846726","https://openalex.org/W2965481926","https://openalex.org/W2971487518","https://openalex.org/W2994864039","https://openalex.org/W3017637887","https://openalex.org/W3019754359","https://openalex.org/W3042614399","https://openalex.org/W3043835773","https://openalex.org/W3102660688","https://openalex.org/W3104135675","https://openalex.org/W3109379736","https://openalex.org/W3133650345","https://openalex.org/W3145026833","https://openalex.org/W3160137267","https://openalex.org/W3193597541","https://openalex.org/W4205213185","https://openalex.org/W4205324465","https://openalex.org/W4225658861","https://openalex.org/W4225844297","https://openalex.org/W4226070132","https://openalex.org/W4226078923","https://openalex.org/W4226332633","https://openalex.org/W4226414838","https://openalex.org/W4281257868","https://openalex.org/W4281657029","https://openalex.org/W4292369513","https://openalex.org/W4308652119","https://openalex.org/W4367668587"],"related_works":["https://openalex.org/W1574414179","https://openalex.org/W4362597605","https://openalex.org/W2922073769","https://openalex.org/W4297676672","https://openalex.org/W4281702477","https://openalex.org/W4220972140","https://openalex.org/W3161120485","https://openalex.org/W2810330923","https://openalex.org/W4289763776","https://openalex.org/W4223442957"],"abstract_inverted_index":{"Diabetic":[0],"nephropathy":[1],"(DN)":[2],"in":[3,19,36,77,168],"the":[4,11,20,172,215],"context":[5],"of":[6,14,43,106,136,178,191,204],"type":[7],"2":[8],"diabetes":[9],"is":[10,24],"leading":[12],"cause":[13],"end-stage":[15],"renal":[16],"disease":[17,44],"(ESRD)":[18],"United":[21],"States.":[22],"DN":[23,142],"graded":[25],"based":[26],"on":[27],"glomerular":[28],"morphology":[29],"and":[30,48,61,74,109,129,161,166,201,217,230],"has":[31],"a":[32,87,110,116,122,134,150,210],"spatially":[33,241],"heterogeneous":[34],"presentation":[35],"kidney":[37,138],"biopsies":[38],"that":[39,236],"complicates":[40],"pathologists'":[41],"predictions":[42],"progression.":[45],"Artificial":[46],"intelligence":[47],"deep":[49,123],"learning":[50],"methods":[51],"for":[52,57,115,126,183,239],"pathology":[53,247],"have":[54],"shown":[55],"promise":[56],"quantitative":[58],"pathological":[59],"evaluation":[60],"clinical":[62],"trajectory":[63],"estimation;":[64],"but,":[65],"they":[66],"often":[67],"fail":[68],"to":[69],"capture":[70],"large-scale":[71],"spatial":[72,112],"anatomy":[73],"relationships":[75],"found":[76],"whole":[78],"slide":[79],"images":[80],"(WSIs).":[81],"In":[82],"this":[83],"study,":[84],"we":[85],"present":[86],"transformer-based,":[88],"multi-stage":[89],"ESRD":[90,132],"prediction":[91],"framework":[92,157],"built":[93],"upon":[94],"nonlinear":[95],"dimensionality":[96],"reduction,":[97],"relative":[98,198],"Euclidean":[99],"pixel":[100],"distance":[101,199],"embeddings":[102],"between":[103],"every":[104],"pair":[105],"observable":[107],"glomeruli,":[108],"corresponding":[111],"self-attention":[113],"mechanism":[114],"robust":[117],"contextual":[118],"representation.":[119],"We":[120],"developed":[121],"transformer":[124,156],"network":[125],"encoding":[127],"WSI":[128,243],"predicting":[130,184],"future":[131,240],"using":[133,245],"dataset":[135],"56":[137],"biopsy":[139],"WSIs":[140],"from":[141],"patients":[143],"at":[144],"Seoul":[145],"National":[146],"University":[147],"Hospital.":[148],"Using":[149],"leave-one-out":[151],"cross-validation":[152],"scheme,":[153],"our":[154,197,226],"modified":[155],"outperformed":[158],"RNNs,":[159],"XGBoost,":[160],"logistic":[162],"regression":[163],"baseline":[164],"models,":[165],"resulted":[167],"an":[169,189,202],"area":[170],"under":[171],"receiver":[173],"operating":[174],"characteristic":[175],"curve":[176],"(AUC)":[177],"0.97":[179],"(95%":[180,193,206],"CI:":[181,194,207],"0.90-1.00)":[182],"two-year":[185],"ESRD,":[186],"compared":[187],"with":[188],"AUC":[190,203],"0.86":[192],"0.66-0.99)":[195],"without":[196,209],"embedding,":[200],"0.76":[205],"0.59-0.92)":[208],"denoising":[211],"autoencoder":[212],"module.":[213],"While":[214],"variability":[216],"generalizability":[218],"induced":[219],"by":[220],"smaller":[221],"sample":[222],"sizes":[223],"are":[224],"challenging,":[225],"distance-based":[227],"embedding":[228],"approach":[229],"overfitting":[231],"mitigation":[232],"techniques":[233],"yielded":[234],"results":[235],"suggest":[237],"opportunities":[238],"aware":[242],"research":[244],"limited":[246],"datasets.":[248]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":2}],"updated_date":"2026-08-01T09:00:35.917206","created_date":"2025-10-10T00:00:00"}
