{"id":"https://openalex.org/W4226213830","doi":"https://doi.org/10.1007/s44163-021-00015-z","title":"A novel interaction-based methodology towards explainable AI with better understanding of Pneumonia Chest X-ray Images","display_name":"A novel interaction-based methodology towards explainable AI with better understanding of Pneumonia Chest X-ray Images","publication_year":2021,"publication_date":"2021-12-01","ids":{"openalex":"https://openalex.org/W4226213830","doi":"https://doi.org/10.1007/s44163-021-00015-z"},"language":"en","primary_location":{"id":"doi:10.1007/s44163-021-00015-z","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s44163-021-00015-z","pdf_url":"https://link.springer.com/content/pdf/10.1007/s44163-021-00015-z.pdf","source":{"id":"https://openalex.org/S4210220416","display_name":"Discover Artificial Intelligence","issn_l":"2731-0809","issn":["2731-0809"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319965","host_organization_name":"Springer Nature","host_organization_lineage":["https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Discover Artificial Intelligence","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://link.springer.com/content/pdf/10.1007/s44163-021-00015-z.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5110828480","display_name":"Shaw\u2010Hwa Lo","orcid":null},"institutions":[{"id":"https://openalex.org/I78577930","display_name":"Columbia University","ror":"https://ror.org/00hj8s172","country_code":"US","type":"education","lineage":["https://openalex.org/I78577930"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Shaw-Hwa Lo","raw_affiliation_strings":["Columbia University, New York, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Columbia University, New York, USA","institution_ids":["https://openalex.org/I78577930"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5004876143","display_name":"Yiqiao Yin","orcid":"https://orcid.org/0000-0003-1216-4232"},"institutions":[{"id":"https://openalex.org/I78577930","display_name":"Columbia University","ror":"https://ror.org/00hj8s172","country_code":"US","type":"education","lineage":["https://openalex.org/I78577930"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Yiqiao Yin","raw_affiliation_strings":["Columbia University, New York, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Columbia University, New York, USA","institution_ids":["https://openalex.org/I78577930"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5004876143"],"corresponding_institution_ids":["https://openalex.org/I78577930"],"apc_list":{"value":990,"currency":"EUR","value_usd":1067},"apc_paid":{"value":990,"currency":"EUR","value_usd":1067},"fwci":0.9794,"has_fulltext":true,"cited_by_count":12,"citation_normalized_percentile":{"value":0.8144642,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":98},"biblio":{"volume":"1","issue":"1","first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12026","display_name":"Explainable Artificial Intelligence (XAI)","score":0.9980000257492065,"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/T12026","display_name":"Explainable Artificial Intelligence (XAI)","score":0.9980000257492065,"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":0.9951000213623047,"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/T11775","display_name":"COVID-19 diagnosis using AI","score":0.9860000014305115,"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/interpretability","display_name":"Interpretability","score":0.9729695320129395},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7117737531661987},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.6517841815948486},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6163181066513062},{"id":"https://openalex.org/keywords/field","display_name":"Field (mathematics)","score":0.5661278963088989},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5515753626823425},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5399051308631897},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.5217957496643066},{"id":"https://openalex.org/keywords/visualization","display_name":"Visualization","score":0.4500289261341095},{"id":"https://openalex.org/keywords/focus","display_name":"Focus (optics)","score":0.428700715303421},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.38592734932899475},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.377814382314682},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.1317044198513031}],"concepts":[{"id":"https://openalex.org/C2781067378","wikidata":"https://www.wikidata.org/wiki/Q17027399","display_name":"Interpretability","level":2,"score":0.9729695320129395},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7117737531661987},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6517841815948486},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6163181066513062},{"id":"https://openalex.org/C9652623","wikidata":"https://www.wikidata.org/wiki/Q190109","display_name":"Field (mathematics)","level":2,"score":0.5661278963088989},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5515753626823425},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5399051308631897},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.5217957496643066},{"id":"https://openalex.org/C36464697","wikidata":"https://www.wikidata.org/wiki/Q451553","display_name":"Visualization","level":2,"score":0.4500289261341095},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.428700715303421},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.38592734932899475},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.377814382314682},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.1317044198513031},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C120665830","wikidata":"https://www.wikidata.org/wiki/Q14620","display_name":"Optics","level":1,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C202444582","wikidata":"https://www.wikidata.org/wiki/Q837863","display_name":"Pure mathematics","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1007/s44163-021-00015-z","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s44163-021-00015-z","pdf_url":"https://link.springer.com/content/pdf/10.1007/s44163-021-00015-z.pdf","source":{"id":"https://openalex.org/S4210220416","display_name":"Discover Artificial Intelligence","issn_l":"2731-0809","issn":["2731-0809"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319965","host_organization_name":"Springer Nature","host_organization_lineage":["https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Discover Artificial Intelligence","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:44558236f3c64001aa0517a72c9ba0bb","is_oa":true,"landing_page_url":"https://doaj.org/article/44558236f3c64001aa0517a72c9ba0bb","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","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-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Discover Artificial Intelligence, Vol 1, Iss 1, Pp 1-17 (2021)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1007/s44163-021-00015-z","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s44163-021-00015-z","pdf_url":"https://link.springer.com/content/pdf/10.1007/s44163-021-00015-z.pdf","source":{"id":"https://openalex.org/S4210220416","display_name":"Discover Artificial Intelligence","issn_l":"2731-0809","issn":["2731-0809"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319965","host_organization_name":"Springer Nature","host_organization_lineage":["https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Discover Artificial Intelligence","raw_type":"journal-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/9","display_name":"Industry, innovation and infrastructure","score":0.5}],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4226213830.pdf","grobid_xml":"https://content.openalex.org/works/W4226213830.grobid-xml"},"referenced_works_count":27,"referenced_works":["https://openalex.org/W1524680991","https://openalex.org/W2033171665","https://openalex.org/W2037238448","https://openalex.org/W2091724448","https://openalex.org/W2097117768","https://openalex.org/W2102605133","https://openalex.org/W2123644769","https://openalex.org/W2143461268","https://openalex.org/W2151480498","https://openalex.org/W2154579312","https://openalex.org/W2163605009","https://openalex.org/W2194775991","https://openalex.org/W2295107390","https://openalex.org/W2340690086","https://openalex.org/W2531409750","https://openalex.org/W2558478853","https://openalex.org/W2884261459","https://openalex.org/W2891503716","https://openalex.org/W2891756914","https://openalex.org/W2921073497","https://openalex.org/W2945976633","https://openalex.org/W2952817546","https://openalex.org/W2963095307","https://openalex.org/W2963446712","https://openalex.org/W2984802304","https://openalex.org/W3116286104","https://openalex.org/W3138819813"],"related_works":["https://openalex.org/W2905433371","https://openalex.org/W4390569940","https://openalex.org/W2888392564","https://openalex.org/W4361193272","https://openalex.org/W4310278675","https://openalex.org/W4388422664","https://openalex.org/W2806259446","https://openalex.org/W2963326959","https://openalex.org/W4247136043","https://openalex.org/W4312407344"],"abstract_inverted_index":{"Abstract":[0],"In":[1,77,209],"the":[2,25,37,51,67,80,93,99,137,144,168,179,185,199,203,217],"field":[3],"of":[4,39,53,57,69,79,131,190,206,211,243,256,259],"eXplainable":[5],"AI":[6],"(XAI),":[7],"robust":[8],"\u201cblackbox\u201d":[9],"algorithms":[10,32],"such":[11,232],"as":[12,128,233],"Convolutional":[13],"Neural":[14],"Networks":[15],"(CNNs)":[16],"are":[17,112],"known":[18],"for":[19,171],"making":[20],"high":[21,122],"prediction":[22,186,267],"performance.":[23,187,248],"However,":[24],"ability":[26],"to":[27,115,166,202,245],"explain":[28],"and":[29,71,95,108,159,181,235],"interpret":[30],"these":[31],"still":[33,73],"require":[34,74,239],"innovation":[35],"in":[36,60,98,152],"understanding":[38],"influential":[40],"and,":[41],"more":[42,172],"importantly,":[43],"explainable":[44,107,252],"features":[45,110,120,253],"that":[46,111,197],"directly":[47,113],"or":[48,264],"indirectly":[49],"impact":[50],"performance":[52],"predictivity.":[54,117],"A":[55],"number":[56],"methods":[58],"existing":[59],"literature":[61],"focus":[62],"on":[63,147],"visualization":[64],"techniques":[65],"but":[66],"concepts":[68],"explainability":[70,180],"interpretability":[72,182],"rigorous":[75],"definition.":[76],"view":[78],"above":[81],"needs,":[82],"this":[83,191],"paper":[84,192],"proposes":[85],"an":[86,104],"interaction-based":[87,140],"methodology\u2013Influence":[88],"score":[89],"(I-score)\u2014to":[90],"screen":[91],"out":[92],"noisy":[94],"non-informative":[96],"variables":[97,132],"images":[100],"hence":[101,136],"it":[102],"nourishes":[103],"environment":[105],"with":[106,121,133],"interpretable":[109],"associated":[114],"feature":[116],"The":[118,188],"selected":[119,251],"I-score":[123,250],"values":[124],"can":[125],"be":[126],"considered":[127],"a":[129,148,194],"group":[130],"interactive":[134],"effect,":[135],"proposed":[138,145,169,218],"name":[139],"methodology.":[141],"We":[142,163],"apply":[143,167],"method":[146,219],"real":[149],"world":[150],"application":[151],"Pneumonia":[153,212],"Chest":[154,213],"X-ray":[155,214],"Image":[156,215],"data":[157,175],"set":[158],"produced":[160],"state-of-the-art":[161],"results.":[162,268],"demonstrate":[164],"how":[165],"approach":[170],"general":[173],"big":[174],"problems":[176],"by":[177],"improving":[178],"without":[183],"sacrificing":[184],"contribution":[189],"opens":[193],"novel":[195],"angle":[196],"moves":[198],"community":[200],"closer":[201],"future":[204],"pipelines":[205],"XAI":[207],"problems.":[208],"investigation":[210],"data,":[216],"achieves":[220],"99.7%":[221],"Area-Under-Curve":[222],"(AUC)":[223],"using":[224],"less":[225],"than":[226],"20,000":[227],"parameters":[228,244,260],"while":[229,261],"its":[230,236],"peers":[231],"VGG16":[234],"upgraded":[237],"versions":[238],"at":[240],"least":[241],"millions":[242],"achieve":[246],"on-par":[247],"Using":[249],"allows":[254],"reduction":[255],"over":[257],"98%":[258],"delivering":[262],"same":[263],"even":[265],"better":[266]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":4},{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":3},{"year":2022,"cited_by_count":1}],"updated_date":"2026-05-21T06:26:12.895304","created_date":"2025-10-10T00:00:00"}
