{"id":"https://openalex.org/W7162655162","doi":"https://doi.org/10.48550/arxiv.2605.28060","title":"Challenges in Explaining Pretrained Clinical Text Classifiers","display_name":"Challenges in Explaining Pretrained Clinical Text Classifiers","publication_year":2026,"publication_date":"2026-05-27","ids":{"openalex":"https://openalex.org/W7162655162","doi":"https://doi.org/10.48550/arxiv.2605.28060"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2605.28060","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.28060","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":false,"raw_source_name":null,"raw_type":"article"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2605.28060","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5015799203","display_name":"Kristian Miok","orcid":"https://orcid.org/0000-0002-1748-8546"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Miok, Kristian","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5020887390","display_name":"Matej Klemen","orcid":"https://orcid.org/0000-0002-7852-2357"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Klemen, Matej","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5007096285","display_name":"Bla\u017e \u0160krlj","orcid":"https://orcid.org/0000-0002-9916-8756"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"\u0160krlj, Blaz","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5020021079","display_name":"Marko Robnik\u2010\u0160ikonja","orcid":"https://orcid.org/0000-0002-1232-3320"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"\u0160ikonja, Marko Robnik","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":4,"corresponding_author_ids":[],"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/T13702","display_name":"Machine Learning in Healthcare","score":0.5170000195503235,"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/T13702","display_name":"Machine Learning in Healthcare","score":0.5170000195503235,"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":0.1363999992609024,"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/T11636","display_name":"Artificial Intelligence in Healthcare and Education","score":0.10530000180006027,"subfield":{"id":"https://openalex.org/subfields/2718","display_name":"Health Informatics"},"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/clinical-practice","display_name":"Clinical Practice","score":0.35040000081062317},{"id":"https://openalex.org/keywords/core","display_name":"Core (optical fiber)","score":0.34630000591278076},{"id":"https://openalex.org/keywords/margin","display_name":"Margin (machine learning)","score":0.31859999895095825},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.26109999418258667}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6118999719619751},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5091999769210815},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.4860999882221222},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3889000117778778},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.35269999504089355},{"id":"https://openalex.org/C2779974597","wikidata":"https://www.wikidata.org/wiki/Q28448986","display_name":"Clinical Practice","level":2,"score":0.35040000081062317},{"id":"https://openalex.org/C2164484","wikidata":"https://www.wikidata.org/wiki/Q5170150","display_name":"Core (optical fiber)","level":2,"score":0.34630000591278076},{"id":"https://openalex.org/C774472","wikidata":"https://www.wikidata.org/wiki/Q6760393","display_name":"Margin (machine learning)","level":2,"score":0.31859999895095825},{"id":"https://openalex.org/C180747234","wikidata":"https://www.wikidata.org/wiki/Q23373","display_name":"Cognitive psychology","level":1,"score":0.26409998536109924},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.26109999418258667}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2605.28060","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.28060","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":"doi:10.48550/arxiv.2605.28060","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.28060","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":false,"raw_source_name":null,"raw_type":"article"},"sustainable_development_goals":[{"score":0.7883327603340149,"id":"https://metadata.un.org/sdg/4","display_name":"Quality Education"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Explaining":[0],"the":[1,88],"predictions":[2,80],"of":[3,48],"neural":[4],"models":[5],"in":[6,75],"clinical":[7,39],"NLP":[8],"remains":[9],"a":[10,59],"significant":[11],"challenge,":[12],"especially":[13],"for":[14,81,90],"complex":[15],"tasks":[16],"involving":[17],"long,":[18],"unstructured":[19],"medical":[20],"texts.":[21],"While":[22],"post-hoc":[23],"methods":[24],"like":[25],"LIME":[26],"and":[27,50,78,100],"SHAP":[28],"are":[29,94],"widely":[30],"used,":[31],"they":[32],"often":[33],"fall":[34],"short":[35],"when":[36],"applied":[37],"to":[38,102],"narratives.":[40],"In":[41],"this":[42],"paper,":[43],"we":[44],"identify":[45],"core":[46],"limitations":[47],"token-level":[49],"perturbation-based":[51],"explanation":[52,91],"techniques":[53],"through":[54],"targeted":[55],"demonstra-":[56],"tions":[57],"on":[58,71],"hospital":[60],"length-of-stay":[61],"prediction":[62],"task.":[63],"Our":[64],"findings":[65],"reveal":[66],"issues":[67],"such":[68],"as":[69],"overemphasis":[70],"non-informative":[72],"tokens,":[73],"instability":[74],"at-":[76],"tributions,":[77],"high-confidence":[79],"incoherent":[82],"input":[83],"variants.":[84],"These":[85],"results":[86],"underscore":[87],"need":[89],"strategies":[92],"that":[93],"clin-":[95],"ically":[96],"meaningful,":[97],"semantically":[98],"grounded,":[99],"robust":[101],"linguistic":[103],"noise.":[104]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2026-05-29T00:00:00"}