{"id":"https://openalex.org/W4400113177","doi":"https://doi.org/10.1109/mipro60963.2024.10569875","title":"Processing Medical Diagnostic Reports using Machine Learning","display_name":"Processing Medical Diagnostic Reports using Machine Learning","publication_year":2024,"publication_date":"2024-05-20","ids":{"openalex":"https://openalex.org/W4400113177","doi":"https://doi.org/10.1109/mipro60963.2024.10569875"},"language":"en","primary_location":{"id":"doi:10.1109/mipro60963.2024.10569875","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/mipro60963.2024.10569875","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 47th MIPRO ICT and Electronics Convention (MIPRO)","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5099635162","display_name":"M\u00e1ria Kraj\u010d\u00ed","orcid":null},"institutions":[{"id":"https://openalex.org/I154347574","display_name":"University of Rijeka","ror":"https://ror.org/05r8dqr10","country_code":"HR","type":"education","lineage":["https://openalex.org/I154347574"]}],"countries":["HR"],"is_corresponding":true,"raw_author_name":"M\u00e1ria Kraj\u010d\u00ed","raw_affiliation_strings":["University of Rijeka,Faculty of Engineering,Rijeka,Croatia"],"affiliations":[{"raw_affiliation_string":"University of Rijeka,Faculty of Engineering,Rijeka,Croatia","institution_ids":["https://openalex.org/I154347574"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5062433563","display_name":"Mateja Napravnik","orcid":"https://orcid.org/0000-0002-3271-3342"},"institutions":[{"id":"https://openalex.org/I154347574","display_name":"University of Rijeka","ror":"https://ror.org/05r8dqr10","country_code":"HR","type":"education","lineage":["https://openalex.org/I154347574"]}],"countries":["HR"],"is_corresponding":false,"raw_author_name":"Mateja Napravnik","raw_affiliation_strings":["University of Rijeka,Faculty of Engineering,Rijeka,Croatia"],"affiliations":[{"raw_affiliation_string":"University of Rijeka,Faculty of Engineering,Rijeka,Croatia","institution_ids":["https://openalex.org/I154347574"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5081398821","display_name":"Ivan \u0160tajduhar","orcid":"https://orcid.org/0000-0003-4758-7972"},"institutions":[{"id":"https://openalex.org/I154347574","display_name":"University of Rijeka","ror":"https://ror.org/05r8dqr10","country_code":"HR","type":"education","lineage":["https://openalex.org/I154347574"]}],"countries":["HR"],"is_corresponding":false,"raw_author_name":"Ivan \u0160tajduhar","raw_affiliation_strings":["University of Rijeka,Faculty of Engineering,Rijeka,Croatia"],"affiliations":[{"raw_affiliation_string":"University of Rijeka,Faculty of Engineering,Rijeka,Croatia","institution_ids":["https://openalex.org/I154347574"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5099635162"],"corresponding_institution_ids":["https://openalex.org/I154347574"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.1175406,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"1904","issue":null,"first_page":"114","last_page":"119"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11396","display_name":"Artificial Intelligence in Healthcare","score":0.9884999990463257,"subfield":{"id":"https://openalex.org/subfields/3605","display_name":"Health Information Management"},"field":{"id":"https://openalex.org/fields/36","display_name":"Health Professions"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},"topics":[{"id":"https://openalex.org/T11396","display_name":"Artificial Intelligence in Healthcare","score":0.9884999990463257,"subfield":{"id":"https://openalex.org/subfields/3605","display_name":"Health Information Management"},"field":{"id":"https://openalex.org/fields/36","display_name":"Health Professions"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},{"id":"https://openalex.org/T13702","display_name":"Machine Learning in Healthcare","score":0.9883999824523926,"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":0.9811999797821045,"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/computer-science","display_name":"Computer science","score":0.7621644735336304},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.49769070744514465},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4291669726371765}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7621644735336304},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.49769070744514465},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4291669726371765}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/mipro60963.2024.10569875","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/mipro60963.2024.10569875","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 47th MIPRO ICT and Electronics Convention (MIPRO)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":22,"referenced_works":["https://openalex.org/W1987971958","https://openalex.org/W2101234009","https://openalex.org/W2119821739","https://openalex.org/W2601243251","https://openalex.org/W2786672974","https://openalex.org/W2899726460","https://openalex.org/W2972734857","https://openalex.org/W2980282514","https://openalex.org/W3003257820","https://openalex.org/W3013829950","https://openalex.org/W3021053579","https://openalex.org/W3104613320","https://openalex.org/W3153208071","https://openalex.org/W4285733601","https://openalex.org/W4295830359","https://openalex.org/W4385966080","https://openalex.org/W6747481501","https://openalex.org/W6748816842","https://openalex.org/W6755207826","https://openalex.org/W6761334336","https://openalex.org/W6768817161","https://openalex.org/W6856320727"],"related_works":["https://openalex.org/W2961085424","https://openalex.org/W4306674287","https://openalex.org/W3046775127","https://openalex.org/W3107602296","https://openalex.org/W4394896187","https://openalex.org/W3170094116","https://openalex.org/W4386462264","https://openalex.org/W4364306694","https://openalex.org/W4312192474","https://openalex.org/W4283697347"],"abstract_inverted_index":{"Given":[0],"the":[1,8,53,91,110,116,132,137,142,150,173],"increasing":[2],"number":[3],"of":[4,10,41,55,64,70,90,139,149,164,175],"narrative":[5],"radiology":[6,72],"reports,":[7,92],"task":[9],"linking":[11],"these":[12],"to":[13,86,128,180],"diagnoses":[14],"is":[15],"becoming":[16],"progressively":[17],"more":[18,184],"challenging,":[19],"making":[20],"classification":[21,68,147],"and":[22,31,43,59,84,100,103,122,130,162],"keyword":[23],"analysis":[24],"inevitable.":[25],"Computational":[26],"methods,":[27],"including":[28],"unsupervised":[29],"learning":[30],"natural":[32],"language":[33,81],"processing,":[34],"are":[35,167],"a":[36,46,56,145],"tool":[37],"for":[38,109,183],"automatic":[39],"discovery":[40],"patterns":[42],"keywords":[44,108],"in":[45,141,155],"given":[47],"text.":[48],"This":[49],"paper":[50],"focuses":[51],"on":[52],"application":[54],"transformer":[57,75],"model":[58,76,156],"hierarchical":[60],"density-based":[61],"spatial":[62],"clustering":[63],"applications":[65],"with":[66,144],"noise":[67],"(HDBSCAN)":[69],"unstructured":[71],"reports.":[73],"The":[74,107,134],"was":[77],"trained":[78],"using":[79,96,105,115],"masked":[80],"modeling":[82],"(MLM),":[83],"used":[85],"obtain":[87],"latent":[88],"embeddings":[89],"which":[93],"were":[94,113],"reduced":[95],"uniform":[97],"manifold":[98],"approximation":[99],"projection":[101],"(UMAP),":[102],"clustered":[104],"HDBSCAN.":[106],"individual":[111],"clusters":[112,140],"determined":[114],"term":[117],"frequency-inverse":[118],"document":[119],"frequency":[120],"(TF-IDF)":[121],"support":[123],"vector":[124],"machine":[125],"(SVM)":[126],"weights":[127],"explain":[129],"analyse":[131],"clustering.":[133],"results":[135],"show":[136],"diversity":[138],"dataset,":[143],"high":[146],"accuracy":[148],"linear":[151],"SVM.":[152],"However,":[153],"shortcomings":[154],"evaluation":[157,165],"indicate":[158],"that":[159,172],"further":[160],"research":[161],"optimisation":[163],"metrics":[166],"needed.":[168],"Keyword":[169],"extraction":[170],"shows":[171],"process":[174],"extracting":[176],"relevant":[177],"words":[178],"needs":[179],"be":[181],"improved":[182],"accurate":[185],"classification.":[186]},"counts_by_year":[],"updated_date":"2025-12-26T23:08:49.675405","created_date":"2025-10-10T00:00:00"}