{"id":"https://openalex.org/W4415324618","doi":"https://doi.org/10.1007/978-3-032-08333-3_7","title":"Explanations for\u00a0Medical Diagnosis Predictions Based on\u00a0Argumentation Schemes","display_name":"Explanations for\u00a0Medical Diagnosis Predictions Based on\u00a0Argumentation Schemes","publication_year":2025,"publication_date":"2025-10-18","ids":{"openalex":"https://openalex.org/W4415324618","doi":"https://doi.org/10.1007/978-3-032-08333-3_7"},"language":"en","primary_location":{"id":"doi:10.1007/978-3-032-08333-3_7","is_oa":true,"landing_page_url":"https://doi.org/10.1007/978-3-032-08333-3_7","pdf_url":"https://link.springer.com/content/pdf/10.1007/978-3-032-08333-3_7.pdf","source":{"id":"https://openalex.org/S2764900261","display_name":"Communications in computer and information science","issn_l":"1865-0929","issn":["1865-0929","1865-0937"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"book series"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Communications in Computer and Information Science","raw_type":"book-chapter"},"type":"book-chapter","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://link.springer.com/content/pdf/10.1007/978-3-032-08333-3_7.pdf","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5120005213","display_name":"Felix Liedeker","orcid":"https://orcid.org/0009-0006-2556-9430"},"institutions":[{"id":"https://openalex.org/I20121455","display_name":"Bielefeld University","ror":"https://ror.org/02hpadn98","country_code":"DE","type":"education","lineage":["https://openalex.org/I20121455"]}],"countries":["DE"],"is_corresponding":true,"raw_author_name":"Felix Liedeker","raw_affiliation_strings":["Semantic Computing Group, CITEC, Bielefeld University, Bielefeld, Germany"],"raw_orcid":"https://orcid.org/0009-0006-2556-9430","affiliations":[{"raw_affiliation_string":"Semantic Computing Group, CITEC, Bielefeld University, Bielefeld, Germany","institution_ids":["https://openalex.org/I20121455"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5065966412","display_name":"Olivia Sanchez-Graillet","orcid":"https://orcid.org/0000-0003-3483-265X"},"institutions":[{"id":"https://openalex.org/I20121455","display_name":"Bielefeld University","ror":"https://ror.org/02hpadn98","country_code":"DE","type":"education","lineage":["https://openalex.org/I20121455"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Olivia Sanchez-Graillet","raw_affiliation_strings":["Semantic Computing Group, CITEC, Bielefeld University, Bielefeld, Germany"],"raw_orcid":"https://orcid.org/0000-0003-3483-265X","affiliations":[{"raw_affiliation_string":"Semantic Computing Group, CITEC, Bielefeld University, Bielefeld, Germany","institution_ids":["https://openalex.org/I20121455"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5070424111","display_name":"Christian Brandt","orcid":"https://orcid.org/0000-0001-8666-1640"},"institutions":[{"id":"https://openalex.org/I4210131029","display_name":"Klinikum Bielefeld","ror":"https://ror.org/036d7m178","country_code":"DE","type":"healthcare","lineage":["https://openalex.org/I4210131029"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Christian Brandt","raw_affiliation_strings":["Medical School and University Medical Center OWL, Mara Hospital, Department of Epileptology, Bielefeld University, Bielefeld, Germany"],"raw_orcid":"https://orcid.org/0000-0001-8666-1640","affiliations":[{"raw_affiliation_string":"Medical School and University Medical Center OWL, Mara Hospital, Department of Epileptology, Bielefeld University, Bielefeld, Germany","institution_ids":["https://openalex.org/I4210131029"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5011215491","display_name":"J\u00f6rg Wellmer","orcid":"https://orcid.org/0000-0003-2919-0496"},"institutions":[{"id":"https://openalex.org/I4210112654","display_name":"Universit\u00e4tsklinikum Knappschaftskrankenhaus Bochum","ror":"https://ror.org/024j3hn90","country_code":"DE","type":"healthcare","lineage":["https://openalex.org/I2799784675","https://openalex.org/I4210112654"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"J\u00f6rg Wellmer","raw_affiliation_strings":["Ruhr-Epileptology, University Hospital Knappschaftskrankenhaus Bochum, Ruhr-University, Bochum, Germany"],"raw_orcid":"https://orcid.org/0000-0003-2919-0496","affiliations":[{"raw_affiliation_string":"Ruhr-Epileptology, University Hospital Knappschaftskrankenhaus Bochum, Ruhr-University, Bochum, Germany","institution_ids":["https://openalex.org/I4210112654"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5056086147","display_name":"Philipp Cimiano","orcid":"https://orcid.org/0000-0002-4771-441X"},"institutions":[{"id":"https://openalex.org/I20121455","display_name":"Bielefeld University","ror":"https://ror.org/02hpadn98","country_code":"DE","type":"education","lineage":["https://openalex.org/I20121455"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Philipp Cimiano","raw_affiliation_strings":["Semantic Computing Group, CITEC, Bielefeld University, Bielefeld, Germany"],"raw_orcid":"https://orcid.org/0000-0002-4771-441X","affiliations":[{"raw_affiliation_string":"Semantic Computing Group, CITEC, Bielefeld University, Bielefeld, Germany","institution_ids":["https://openalex.org/I20121455"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5120005213"],"corresponding_institution_ids":["https://openalex.org/I20121455"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.47643122,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"138","last_page":"158"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12026","display_name":"Explainable Artificial Intelligence (XAI)","score":0.998199999332428,"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":0.998199999332428,"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/T10028","display_name":"Topic Modeling","score":0.9966999888420105,"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/T13702","display_name":"Machine Learning in Healthcare","score":0.9908000230789185,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/interpretability","display_name":"Interpretability","score":0.857699990272522},{"id":"https://openalex.org/keywords/argumentation-theory","display_name":"Argumentation theory","score":0.6542999744415283},{"id":"https://openalex.org/keywords/transparency","display_name":"Transparency (behavior)","score":0.555899977684021},{"id":"https://openalex.org/keywords/argumentative","display_name":"Argumentative","score":0.5467000007629395},{"id":"https://openalex.org/keywords/scheme","display_name":"Scheme (mathematics)","score":0.508400022983551},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.5008000135421753},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.4830000102519989}],"concepts":[{"id":"https://openalex.org/C2781067378","wikidata":"https://www.wikidata.org/wiki/Q17027399","display_name":"Interpretability","level":2,"score":0.857699990272522},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.701200008392334},{"id":"https://openalex.org/C65059942","wikidata":"https://www.wikidata.org/wiki/Q270105","display_name":"Argumentation theory","level":2,"score":0.6542999744415283},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6079999804496765},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.6068000197410583},{"id":"https://openalex.org/C2780233690","wikidata":"https://www.wikidata.org/wiki/Q535347","display_name":"Transparency (behavior)","level":2,"score":0.555899977684021},{"id":"https://openalex.org/C2781306805","wikidata":"https://www.wikidata.org/wiki/Q4789761","display_name":"Argumentative","level":2,"score":0.5467000007629395},{"id":"https://openalex.org/C77618280","wikidata":"https://www.wikidata.org/wiki/Q1155772","display_name":"Scheme (mathematics)","level":2,"score":0.508400022983551},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.5008000135421753},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.4830000102519989},{"id":"https://openalex.org/C534262118","wikidata":"https://www.wikidata.org/wiki/Q177719","display_name":"Medical diagnosis","level":2,"score":0.4699000120162964},{"id":"https://openalex.org/C44492722","wikidata":"https://www.wikidata.org/wiki/Q327069","display_name":"Conditional probability","level":2,"score":0.4156000018119812},{"id":"https://openalex.org/C33724603","wikidata":"https://www.wikidata.org/wiki/Q812540","display_name":"Bayesian network","level":2,"score":0.3865000009536743},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.3833000063896179},{"id":"https://openalex.org/C160234255","wikidata":"https://www.wikidata.org/wiki/Q812535","display_name":"Bayesian inference","level":3,"score":0.36660000681877136},{"id":"https://openalex.org/C49937458","wikidata":"https://www.wikidata.org/wiki/Q2599292","display_name":"Probabilistic logic","level":2,"score":0.296099990606308},{"id":"https://openalex.org/C58328972","wikidata":"https://www.wikidata.org/wiki/Q184609","display_name":"Expert system","level":2,"score":0.28949999809265137},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.2759999930858612},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.26159998774528503}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1007/978-3-032-08333-3_7","is_oa":true,"landing_page_url":"https://doi.org/10.1007/978-3-032-08333-3_7","pdf_url":"https://link.springer.com/content/pdf/10.1007/978-3-032-08333-3_7.pdf","source":{"id":"https://openalex.org/S2764900261","display_name":"Communications in computer and information science","issn_l":"1865-0929","issn":["1865-0929","1865-0937"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"book series"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Communications in Computer and Information Science","raw_type":"book-chapter"}],"best_oa_location":{"id":"doi:10.1007/978-3-032-08333-3_7","is_oa":true,"landing_page_url":"https://doi.org/10.1007/978-3-032-08333-3_7","pdf_url":"https://link.springer.com/content/pdf/10.1007/978-3-032-08333-3_7.pdf","source":{"id":"https://openalex.org/S2764900261","display_name":"Communications in computer and information science","issn_l":"1865-0929","issn":["1865-0929","1865-0937"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"book series"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Communications in Computer and Information Science","raw_type":"book-chapter"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G1622223166","display_name":null,"funder_award_id":"438445824","funder_id":"https://openalex.org/F4320320879","funder_display_name":"Deutsche Forschungsgemeinschaft"}],"funders":[{"id":"https://openalex.org/F4320320879","display_name":"Deutsche Forschungsgemeinschaft","ror":"https://ror.org/018mejw64"}],"has_content":{"grobid_xml":false,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4415324618.pdf"},"referenced_works_count":28,"referenced_works":["https://openalex.org/W581684831","https://openalex.org/W1028871446","https://openalex.org/W2104126268","https://openalex.org/W2118022153","https://openalex.org/W2143891888","https://openalex.org/W2237502368","https://openalex.org/W2282821441","https://openalex.org/W2295598076","https://openalex.org/W2394669110","https://openalex.org/W2515196503","https://openalex.org/W2942444880","https://openalex.org/W2962862931","https://openalex.org/W2972025876","https://openalex.org/W3048817558","https://openalex.org/W3124792046","https://openalex.org/W3144635834","https://openalex.org/W3171832026","https://openalex.org/W3212065135","https://openalex.org/W4226445138","https://openalex.org/W4229031370","https://openalex.org/W4230779446","https://openalex.org/W4236137412","https://openalex.org/W4287173734","https://openalex.org/W4298235707","https://openalex.org/W4380201339","https://openalex.org/W4392082904","https://openalex.org/W4396668454","https://openalex.org/W4401072619"],"related_works":[],"abstract_inverted_index":{"Abstract":[0],"As":[1],"(explainable)":[2],"artificial":[3],"intelligence":[4],"becomes":[5],"increasingly":[6],"integrated":[7],"into":[8,102],"high-stakes":[9],"domains":[10],"like":[11],"healthcare,":[12],"it":[13],"is":[14,40,86],"paramount":[15],"to":[16,41],"understand":[17],"what":[18],"makes":[19],"explanations":[20,129],"effective":[21],"and":[22,35,45,122,143,150,160],"convincing.":[23],"In":[24],"this":[25,157],"work,":[26],"we":[27],"propose":[28],"an":[29],"approach":[30],"that":[31,68,105],"integrates":[32],"argumentation":[33,60],"schemes":[34],"Bayesian":[36,95],"networks.":[37],"The":[38,76,127],"goal":[39],"enhance":[42],"the":[43,70,89,115,154],"transparency":[44],"interpretability":[46],"of":[47,156],"medical":[48,74,137],"diagnostic":[49],"decision-making":[50],"based":[51,62],"on":[52,63],"machine":[53],"learning":[54],"models.":[55],"We":[56,152],"design":[57],"a":[58,81,94,110,120,133],"novel":[59],"scheme":[61,67,78],"Walton\u2019s":[64],"abductive":[65],"inference":[66],"captures":[69],"reasoning":[71],"process":[72],"underlying":[73],"diagnoses.":[75],"proposed":[77],"functions":[79],"as":[80],"structured":[82],"explanation":[83],"template,":[84],"which":[85],"instantiated":[87],"with":[88],"conditional":[90,98],"probabilities":[91,99],"derived":[92],"from":[93],"network.":[96],"These":[97],"are":[100],"turned":[101],"statistical":[103],"evidence":[104],"can":[106],"support":[107],"or":[108],"challenge":[109],"conclusion":[111],"made":[112],"explicit":[113],"in":[114,132],"argumentative":[116],"scheme,":[117],"thereby":[118],"providing":[119],"robust":[121],"transparent":[123],"basis":[124],"for":[125,163],"decision-making.":[126],"resulting":[128],"were":[130],"evaluated":[131],"user":[134,158],"study":[135,159],"by":[136],"experts,":[138],"who":[139],"assessed":[140],"their":[141,148],"value":[142],"answered":[144],"targeted":[145],"questions":[146],"about":[147],"usefulness":[149],"clarity.":[151],"present":[153],"results":[155],"provide":[161],"directions":[162],"future":[164],"work.":[165]},"counts_by_year":[],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-19T00:00:00"}
