{"id":"https://openalex.org/W7134061237","doi":"https://doi.org/10.48550/arxiv.2603.04947","title":"Adaptive Prototype-based Interpretable Grading of Prostate Cancer","display_name":"Adaptive Prototype-based Interpretable Grading of Prostate Cancer","publication_year":2026,"publication_date":"2026-03-05","ids":{"openalex":"https://openalex.org/W7134061237","doi":"https://doi.org/10.48550/arxiv.2603.04947"},"language":null,"primary_location":{"id":"pmh:doi:10.48550/arxiv.2603.04947","is_oa":true,"landing_page_url":null,"pdf_url":null,"source":{"id":"https://openalex.org/S4406922384","display_name":"Open MIND","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Article"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":null,"any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5031936968","display_name":"Riddhasree Bhattacharyya","orcid":"https://orcid.org/0009-0007-9824-2874"},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Bhattacharyya, Riddhasree","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5128238802","display_name":"Pallabi Dutta","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Dutta, Pallabi","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5028039397","display_name":"Sushmita Mitra","orcid":"https://orcid.org/0000-0001-9285-1117"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Mitra, Sushmita","raw_affiliation_strings":[],"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5031936968"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10862","display_name":"AI in cancer detection","score":0.47099998593330383,"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":0.47099998593330383,"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/T12026","display_name":"Explainable Artificial Intelligence (XAI)","score":0.27570000290870667,"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/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.08579999953508377,"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/interpretability","display_name":"Interpretability","score":0.913100004196167},{"id":"https://openalex.org/keywords/workflow","display_name":"Workflow","score":0.7067000269889832},{"id":"https://openalex.org/keywords/grading","display_name":"Grading (engineering)","score":0.6539000272750854},{"id":"https://openalex.org/keywords/prostate-cancer","display_name":"Prostate cancer","score":0.6381999850273132},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.3862999975681305},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.33660000562667847},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.3337000012397766}],"concepts":[{"id":"https://openalex.org/C2781067378","wikidata":"https://www.wikidata.org/wiki/Q17027399","display_name":"Interpretability","level":2,"score":0.913100004196167},{"id":"https://openalex.org/C177212765","wikidata":"https://www.wikidata.org/wiki/Q627335","display_name":"Workflow","level":2,"score":0.7067000269889832},{"id":"https://openalex.org/C2777286243","wikidata":"https://www.wikidata.org/wiki/Q5591926","display_name":"Grading (engineering)","level":2,"score":0.6539000272750854},{"id":"https://openalex.org/C2780192828","wikidata":"https://www.wikidata.org/wiki/Q181257","display_name":"Prostate cancer","level":3,"score":0.6381999850273132},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5855000019073486},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.583899974822998},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5242000222206116},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.3862999975681305},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.3774999976158142},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.33660000562667847},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.3337000012397766},{"id":"https://openalex.org/C2778476105","wikidata":"https://www.wikidata.org/wiki/Q628539","display_name":"Workload","level":2,"score":0.3303000032901764},{"id":"https://openalex.org/C2779399171","wikidata":"https://www.wikidata.org/wiki/Q1483951","display_name":"Malignancy","level":2,"score":0.3239000141620636},{"id":"https://openalex.org/C2776235491","wikidata":"https://www.wikidata.org/wiki/Q9625","display_name":"Prostate","level":3,"score":0.32280001044273376},{"id":"https://openalex.org/C153701036","wikidata":"https://www.wikidata.org/wiki/Q659974","display_name":"Trustworthiness","level":2,"score":0.3000999987125397},{"id":"https://openalex.org/C2779466945","wikidata":"https://www.wikidata.org/wiki/Q1765251","display_name":"Prostatectomy","level":4,"score":0.2879999876022339},{"id":"https://openalex.org/C19527891","wikidata":"https://www.wikidata.org/wiki/Q1120908","display_name":"Medical physics","level":1,"score":0.2838999927043915},{"id":"https://openalex.org/C34736171","wikidata":"https://www.wikidata.org/wiki/Q918333","display_name":"Preprocessor","level":2,"score":0.2768000066280365},{"id":"https://openalex.org/C2984842247","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep neural networks","level":3,"score":0.26089999079704285}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:doi:10.48550/arxiv.2603.04947","is_oa":true,"landing_page_url":null,"pdf_url":null,"source":{"id":"https://openalex.org/S4406922384","display_name":"Open MIND","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Article"},{"id":"doi:10.48550/arxiv.2603.04947","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.04947","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"article"}],"best_oa_location":{"id":"pmh:doi:10.48550/arxiv.2603.04947","is_oa":true,"landing_page_url":null,"pdf_url":null,"source":{"id":"https://openalex.org/S4406922384","display_name":"Open MIND","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Article"},"sustainable_development_goals":[{"display_name":"Good health and well-being","score":0.40074753761291504,"id":"https://metadata.un.org/sdg/3"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Prostate":[0],"cancer":[1,63,94,152],"being":[2],"one":[3],"of":[4,32,43,92,114],"the":[5,11,30,74,112,154,188,196],"frequently":[6],"diagnosed":[7],"malignancy":[8],"in":[9,41,53,117,207],"men,":[10],"rising":[12],"demand":[13],"for":[14,50,61,88,150,182,205],"biopsies":[15],"places":[16],"a":[17,66,83,115,147,159,165,201],"severe":[18],"workload":[19],"on":[20,187],"pathologists.":[21],"The":[22,125],"grading":[23,91],"procedure":[24,110],"is":[25,127,156,171],"tedious":[26],"and":[27,191],"subjective,":[28],"motivating":[29],"development":[31],"automated":[33],"systems.":[34],"Although":[35],"deep":[36],"learning":[37],"has":[38],"made":[39],"inroads":[40],"terms":[42],"performance,":[44],"its":[45],"limited":[46],"interpretability":[47,59],"poses":[48],"challenges":[49],"widespread":[51],"adoption":[52],"high-stake":[54],"applications":[55],"like":[56],"medicine.":[57],"Existing":[58],"techniques":[60],"prostate":[62,93,151],"classifiers":[64],"provide":[65],"coarse":[67],"explanation":[68],"but":[69],"do":[70],"not":[71],"reveal":[72],"why":[73],"highlighted":[75],"regions":[76,120],"matter.":[77],"In":[78,141],"this":[79],"scenario,":[80],"we":[81],"propose":[82],"novel":[84],"prototype-based":[85],"weakly-supervised":[86,148],"framework":[87,197],"an":[89],"interpretable":[90],"from":[95],"histopathology":[96],"images.":[97],"These":[98],"networks":[99],"can":[100,198],"prove":[101],"to":[102,132,143,146,173],"be":[103],"more":[104],"trustworthy":[105],"since":[106],"their":[107,208],"explicit":[108],"reasoning":[109],"mirrors":[111],"workflow":[113],"pathologist":[116],"comparing":[118],"suspicious":[119],"with":[121,138,158],"clinically":[122],"validated":[123],"examples.":[124],"network":[126,155],"initially":[128],"pre-trained":[129],"at":[130],"patch-level":[131],"learn":[133],"robust":[134],"prototypical":[135],"features":[136],"associated":[137],"each":[139],"grade.":[140],"order":[142],"adapt":[144],"it":[145],"setup":[149],"grading,":[153],"fine-tuned":[157],"new":[160,166],"prototype-aware":[161],"loss":[162],"function.":[163],"Finally,":[164],"attention-based":[167],"dynamic":[168],"pruning":[169],"mechanism":[170],"introduced":[172],"handle":[174],"inter-sample":[175],"heterogeneity,":[176],"while":[177],"selectively":[178],"emphasizing":[179],"relevant":[180],"prototypes":[181],"optimal":[183],"performance.":[184],"Extensive":[185],"validation":[186],"benchmark":[189],"PANDA":[190],"SICAP":[192],"datasets":[193],"confirms":[194],"that":[195],"serve":[199],"as":[200],"reliable":[202],"assistive":[203],"tool":[204],"pathologists":[206],"routine":[209],"diagnostic":[210],"workflows.":[211]},"counts_by_year":[],"updated_date":"2026-04-04T16:13:02.066488","created_date":"2026-03-07T00:00:00"}