{"id":"https://openalex.org/W6948630830","doi":"https://doi.org/10.48550/arxiv.2508.09991","title":"Bridging AI Innovation and Healthcare Needs: Lessons Learned from Incorporating Modern NLP at The BC Cancer Registry","display_name":"Bridging AI Innovation and Healthcare Needs: Lessons Learned from Incorporating Modern NLP at The BC Cancer Registry","publication_year":2025,"publication_date":"2025-07-27","ids":{"openalex":"https://openalex.org/W6948630830","doi":"https://doi.org/10.48550/arxiv.2508.09991"},"language":"en","primary_location":{"id":"doi:10.48550/arxiv.2508.09991","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2508.09991","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"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":"Preprint"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2508.09991","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Gondara, Lovedeep","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Gondara, Lovedeep","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":null,"display_name":"Arbour, Gregory","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Arbour, Gregory","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":null,"display_name":"Ng, Raymond","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ng, Raymond","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":null,"display_name":"Simkin, Jonathan","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Simkin, Jonathan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":null,"display_name":"Devji, Shebnum","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Devji, Shebnum","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"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":true,"primary_topic":{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.2685999870300293,"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/T10028","display_name":"Topic Modeling","score":0.2685999870300293,"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":0.23109999299049377,"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"}},{"id":"https://openalex.org/T13702","display_name":"Machine Learning in Healthcare","score":0.053700000047683716,"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/bridging","display_name":"Bridging (networking)","score":0.777999997138977},{"id":"https://openalex.org/keywords/health-care","display_name":"Health care","score":0.5691999793052673},{"id":"https://openalex.org/keywords/data-extraction","display_name":"Data extraction","score":0.5401999950408936},{"id":"https://openalex.org/keywords/quality","display_name":"Quality (philosophy)","score":0.45829999446868896},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.4036000072956085},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.400299996137619},{"id":"https://openalex.org/keywords/information-extraction","display_name":"Information extraction","score":0.3456000089645386},{"id":"https://openalex.org/keywords/data-quality","display_name":"Data quality","score":0.3402000069618225}],"concepts":[{"id":"https://openalex.org/C174348530","wikidata":"https://www.wikidata.org/wiki/Q188635","display_name":"Bridging (networking)","level":2,"score":0.777999997138977},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5770000219345093},{"id":"https://openalex.org/C160735492","wikidata":"https://www.wikidata.org/wiki/Q31207","display_name":"Health care","level":2,"score":0.5691999793052673},{"id":"https://openalex.org/C2777466982","wikidata":"https://www.wikidata.org/wiki/Q5227287","display_name":"Data extraction","level":3,"score":0.5401999950408936},{"id":"https://openalex.org/C56739046","wikidata":"https://www.wikidata.org/wiki/Q192060","display_name":"Knowledge management","level":1,"score":0.49540001153945923},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4814000129699707},{"id":"https://openalex.org/C2779530757","wikidata":"https://www.wikidata.org/wiki/Q1207505","display_name":"Quality (philosophy)","level":2,"score":0.45829999446868896},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.45719999074935913},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.4036000072956085},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.400299996137619},{"id":"https://openalex.org/C195807954","wikidata":"https://www.wikidata.org/wiki/Q1662562","display_name":"Information extraction","level":2,"score":0.3456000089645386},{"id":"https://openalex.org/C24756922","wikidata":"https://www.wikidata.org/wiki/Q1757694","display_name":"Data quality","level":3,"score":0.3402000069618225},{"id":"https://openalex.org/C71405471","wikidata":"https://www.wikidata.org/wiki/Q757012","display_name":"Quality management","level":3,"score":0.32429999113082886},{"id":"https://openalex.org/C81917197","wikidata":"https://www.wikidata.org/wiki/Q628760","display_name":"Selection (genetic algorithm)","level":2,"score":0.32249999046325684},{"id":"https://openalex.org/C61904560","wikidata":"https://www.wikidata.org/wiki/Q1148359","display_name":"Grey literature","level":3,"score":0.31209999322891235},{"id":"https://openalex.org/C75684735","wikidata":"https://www.wikidata.org/wiki/Q858810","display_name":"Big data","level":2,"score":0.3111000061035156},{"id":"https://openalex.org/C184356942","wikidata":"https://www.wikidata.org/wiki/Q830382","display_name":"Best practice","level":2,"score":0.3043000102043152},{"id":"https://openalex.org/C207685749","wikidata":"https://www.wikidata.org/wiki/Q2088941","display_name":"Domain knowledge","level":2,"score":0.2946999967098236},{"id":"https://openalex.org/C145642194","wikidata":"https://www.wikidata.org/wiki/Q870895","display_name":"Health informatics","level":3,"score":0.2766000032424927},{"id":"https://openalex.org/C539667460","wikidata":"https://www.wikidata.org/wiki/Q2414942","display_name":"Management science","level":1,"score":0.27140000462532043},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.26759999990463257},{"id":"https://openalex.org/C195094911","wikidata":"https://www.wikidata.org/wiki/Q14167904","display_name":"Process management","level":1,"score":0.2655999958515167},{"id":"https://openalex.org/C158154518","wikidata":"https://www.wikidata.org/wiki/Q7310970","display_name":"Relevance (law)","level":2,"score":0.2651999890804291},{"id":"https://openalex.org/C2775860198","wikidata":"https://www.wikidata.org/wiki/Q7257872","display_name":"Public hospital","level":2,"score":0.26489999890327454},{"id":"https://openalex.org/C2779473830","wikidata":"https://www.wikidata.org/wiki/Q1540899","display_name":"MEDLINE","level":2,"score":0.26350000500679016}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2508.09991","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2508.09991","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"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":"Preprint"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2508.09991","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2508.09991","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"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":"Preprint"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/4","score":0.8757039308547974,"display_name":"Quality Education"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Automating":[0],"data":[1,116,156],"extraction":[2,35],"from":[3,94],"clinical":[4],"documents":[5],"offers":[6],"significant":[7],"potential":[8],"to":[9,78,115,149,154],"improve":[10,161],"efficiency":[11],"in":[12],"healthcare":[13,146],"settings,":[14],"yet":[15],"deploying":[16],"Natural":[17],"Language":[18],"Processing":[19],"(NLP)":[20],"solutions":[21,153],"presents":[22],"practical":[23,137],"challenges.":[24],"Drawing":[25],"upon":[26],"our":[27],"experience":[28],"implementing":[29],"various":[30],"NLP":[31],"models":[32],"for":[33,101,145],"information":[34],"and":[36,80,85,91,108,128,131,159,164],"classification":[37],"tasks":[38],"at":[39],"the":[40,53,58,99],"British":[41],"Columbia":[42],"Cancer":[43],"Registry":[44],"(BCCR),":[45],"this":[46],"paper":[47],"shares":[48],"key":[49],"lessons":[50],"learned":[51],"throughout":[52],"project":[54],"lifecycle.":[55],"We":[56],"emphasize":[57],"critical":[59],"importance":[60],"of":[61],"defining":[62],"problems":[63],"based":[64],"on":[65],"clear":[66],"business":[67],"objectives":[68],"rather":[69],"than":[70],"solely":[71],"technical":[72],"accuracy,":[73],"adopting":[74],"an":[75],"iterative":[76],"approach":[77],"development,":[79],"fostering":[81],"deep":[82],"interdisciplinary":[83],"collaboration":[84],"co-design":[86],"involving":[87,125],"domain":[88],"experts,":[89],"end-users,":[90],"ML":[92],"specialists":[93],"inception.":[95],"Further":[96],"insights":[97],"highlight":[98],"need":[100],"pragmatic":[102],"model":[103],"selection":[104],"(including":[105],"hybrid":[106],"approaches":[107],"simpler":[109],"methods":[110],"where":[111],"appropriate),":[112],"rigorous":[113],"attention":[114],"quality":[117],"(representativeness,":[118],"drift,":[119],"annotation),":[120],"robust":[121],"error":[122],"mitigation":[123],"strategies":[124],"human-in-the-loop":[126],"validation":[127],"ongoing":[129],"audits,":[130],"building":[132],"organizational":[133],"AI":[134],"literacy.":[135],"These":[136],"considerations,":[138],"generalizable":[139],"beyond":[140],"cancer":[141],"registries,":[142],"provide":[143],"guidance":[144],"organizations":[147],"seeking":[148],"successfully":[150],"implement":[151],"AI/NLP":[152],"enhance":[155],"management":[157],"processes":[158],"ultimately":[160],"patient":[162],"care":[163],"public":[165],"health":[166],"outcomes.":[167]},"counts_by_year":[],"updated_date":"2026-07-28T07:46:37.118299","created_date":"2025-10-10T00:00:00"}