{"id":"https://openalex.org/W4375868992","doi":"https://doi.org/10.1109/icassp49357.2023.10096190","title":"Position-Aware Graph-Based Learning of Whole Slide Images","display_name":"Position-Aware Graph-Based Learning of Whole Slide Images","publication_year":2023,"publication_date":"2023-05-05","ids":{"openalex":"https://openalex.org/W4375868992","doi":"https://doi.org/10.1109/icassp49357.2023.10096190"},"language":"en","primary_location":{"id":"doi:10.1109/icassp49357.2023.10096190","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/icassp49357.2023.10096190","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICASSP 2023 - 2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","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/A5075546863","display_name":"Milan Aryal","orcid":"https://orcid.org/0009-0005-1326-9804"},"institutions":[{"id":"https://openalex.org/I102461120","display_name":"Marquette University","ror":"https://ror.org/04gr4te78","country_code":"US","type":"education","lineage":["https://openalex.org/I102461120"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Milan Aryal","raw_affiliation_strings":["Marquette University,Department of Computer Science,Milwaukee,USA","Department of Computer Science, Marquette University, Milwaukee, USA"],"affiliations":[{"raw_affiliation_string":"Marquette University,Department of Computer Science,Milwaukee,USA","institution_ids":["https://openalex.org/I102461120"]},{"raw_affiliation_string":"Department of Computer Science, Marquette University, Milwaukee, USA","institution_ids":["https://openalex.org/I102461120"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5038366215","display_name":"Nasim Soltani","orcid":"https://orcid.org/0000-0002-8709-653X"},"institutions":[{"id":"https://openalex.org/I102461120","display_name":"Marquette University","ror":"https://ror.org/04gr4te78","country_code":"US","type":"education","lineage":["https://openalex.org/I102461120"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Nasim Yahya Soltani","raw_affiliation_strings":["Marquette University,Department of Computer Science,Milwaukee,USA","Department of Computer Science, Marquette University, Milwaukee, USA"],"affiliations":[{"raw_affiliation_string":"Marquette University,Department of Computer Science,Milwaukee,USA","institution_ids":["https://openalex.org/I102461120"]},{"raw_affiliation_string":"Department of Computer Science, Marquette University, Milwaukee, USA","institution_ids":["https://openalex.org/I102461120"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5075546863"],"corresponding_institution_ids":["https://openalex.org/I102461120"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.04144297,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"97","issue":null,"first_page":"1","last_page":"5"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10862","display_name":"AI in cancer detection","score":0.9998999834060669,"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"}},"topics":[{"id":"https://openalex.org/T10862","display_name":"AI in cancer detection","score":0.9998999834060669,"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/T10824","display_name":"Image Retrieval and Classification Techniques","score":0.9951000213623047,"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/T12422","display_name":"Radiomics and Machine Learning in Medical Imaging","score":0.9944999814033508,"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/computer-science","display_name":"Computer science","score":0.7397484183311462},{"id":"https://openalex.org/keywords/embedding","display_name":"Embedding","score":0.6272988319396973},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.5893762111663818},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.572090208530426},{"id":"https://openalex.org/keywords/graph-embedding","display_name":"Graph embedding","score":0.5574395060539246},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.5259302258491516},{"id":"https://openalex.org/keywords/encode","display_name":"ENCODE","score":0.503013551235199},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.49621087312698364},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.4355047941207886},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.3159583806991577}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7397484183311462},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.6272988319396973},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.5893762111663818},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.572090208530426},{"id":"https://openalex.org/C75564084","wikidata":"https://www.wikidata.org/wiki/Q5597085","display_name":"Graph embedding","level":3,"score":0.5574395060539246},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.5259302258491516},{"id":"https://openalex.org/C66746571","wikidata":"https://www.wikidata.org/wiki/Q1134833","display_name":"ENCODE","level":3,"score":0.503013551235199},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.49621087312698364},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.4355047941207886},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.3159583806991577},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"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/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icassp49357.2023.10096190","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/icassp49357.2023.10096190","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICASSP 2023 - 2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.5,"display_name":"Good health and well-being","id":"https://metadata.un.org/sdg/3"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":36,"referenced_works":["https://openalex.org/W2037789405","https://openalex.org/W2194775991","https://openalex.org/W2304298711","https://openalex.org/W2327422911","https://openalex.org/W2531897166","https://openalex.org/W2762672048","https://openalex.org/W2768308213","https://openalex.org/W2908510526","https://openalex.org/W2921675148","https://openalex.org/W2951659295","https://openalex.org/W2952575904","https://openalex.org/W2956228567","https://openalex.org/W2964015378","https://openalex.org/W3005680577","https://openalex.org/W3010855850","https://openalex.org/W3028078009","https://openalex.org/W3034534840","https://openalex.org/W3090852973","https://openalex.org/W3099546855","https://openalex.org/W3145450063","https://openalex.org/W3203838058","https://openalex.org/W4205900565","https://openalex.org/W4207066074","https://openalex.org/W4224917531","https://openalex.org/W4288089649","https://openalex.org/W4294558607","https://openalex.org/W4297733535","https://openalex.org/W4312680984","https://openalex.org/W6701327888","https://openalex.org/W6726873649","https://openalex.org/W6738964360","https://openalex.org/W6753331806","https://openalex.org/W6757817989","https://openalex.org/W6763057493","https://openalex.org/W6769428822","https://openalex.org/W6774314701"],"related_works":["https://openalex.org/W4226493464","https://openalex.org/W4312417841","https://openalex.org/W3133861977","https://openalex.org/W2951211570","https://openalex.org/W3103566983","https://openalex.org/W3167935049","https://openalex.org/W3029198973","https://openalex.org/W3036264823","https://openalex.org/W3206528106","https://openalex.org/W2912814903"],"abstract_inverted_index":{"Encoding":[0],"whole":[1],"slide":[2],"images":[3],"(WSI)":[4],"as":[5,10,57],"graphs":[6],"is":[7,93,104,115,136],"well":[8],"motivated":[9],"it":[11],"allows":[12],"the":[13,36,125,129,140,153],"gigapixel":[14],"resolution":[15],"WSI":[16,103,141],"to":[17,123],"be":[18,30,46],"represented":[19],"in":[20,87,131,159],"its":[21],"entirety":[22],"for":[23,48,75,78,143],"learning.":[24],"To":[25],"this":[26,97],"end,":[27],"WSIs":[28],"can":[29,45],"divided":[31],"into":[32],"small":[33],"patches":[34,84],"representing":[35],"nodes":[37,130],"of":[38,100,128,152],"a":[39],"graph.":[40],"Then,":[41],"graph-based":[42],"learning":[43,54],"approaches":[44,158],"deployed":[47],"cancer":[49,101,146,160],"grading":[50,144,163],"and":[51,81,109,147,162],"classification.":[52,133],"Graph-based":[53],"methods":[55],"such":[56],"graph":[58,110,132],"neural":[59,120],"network":[60,121],"(GNN)":[61],"are":[62,85],"based":[63,116],"on":[64,117],"message":[65],"passing":[66],"among":[67],"neighboring":[68],"nodes.":[69],"However,":[70],"they":[71],"do":[72],"not":[73],"account":[74],"positional":[76,107,126],"information":[77],"each":[79],"patch":[80],"if":[82],"two":[83],"located":[86],"topologically":[88],"isomorphic":[89],"neighborhoods,":[90],"their":[91],"embedding":[92,108,127],"almost":[94],"identical.":[95],"In":[96],"work,":[98],"classification":[99],"from":[102],"performed":[105],"with":[106,139,156],"attention.":[111],"The":[112,134],"proposed":[113,154],"approach":[114],"spline":[118],"convolutional":[119],"(CNN)":[122],"encode":[124],"algorithm":[135],"then":[137],"tested":[138],"dataset":[142],"prostate":[145],"kidney":[148],"cancer.":[149],"A":[150],"comparison":[151],"method":[155],"leading":[157],"diagnosis":[161],"verify":[164],"improved":[165],"performance.":[166]},"counts_by_year":[],"updated_date":"2025-12-23T23:11:35.936235","created_date":"2025-10-10T00:00:00"}