{"id":"https://openalex.org/W4416638026","doi":"https://doi.org/10.1183/13993003.congress-2025.pa978","title":"Enhancing Pulmonary Disease Diagnosis with AI. A Study of 5,446 Patients Demonstrating Improved Accuracy and Efficiency in CT Imaging","display_name":"Enhancing Pulmonary Disease Diagnosis with AI. A Study of 5,446 Patients Demonstrating Improved Accuracy and Efficiency in CT Imaging","publication_year":2025,"publication_date":"2025-09-27","ids":{"openalex":"https://openalex.org/W4416638026","doi":"https://doi.org/10.1183/13993003.congress-2025.pa978"},"language":"en","primary_location":{"id":"doi:10.1183/13993003.congress-2025.pa978","doi":"https://doi.org/10.1183/13993003.congress-2025.pa978","is_oa":false,"landing_page_url":"https://doi.org/10.1183/13993003.congress-2025.pa978","pdf_url":null,"source":{"id":"https://openalex.org/S4210207896","display_name":"European Respiratory Journal","issn_l":"0903-1936","issn":["0903-1936","1399-3003"],"is_oa":false,"is_in_doaj":false,"is_core":true,"listed_in":["anvur-class-a","anvur-scientific","cwts-core","dongbi-a","doyens","jufo-3","ki-jl-3","medline","norway-2","poland-200","russia-white-list-1","vabb-shw"],"host_organization":"https://openalex.org/P4310317833","host_organization_name":"European Respiratory Society","host_organization_lineage":["https://openalex.org/P4310317833"],"host_organization_lineage_names":["European Respiratory Society"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Imaging","raw_type":"proceedings-article"},"volume":null,"type":"conference-abstract","is_traditional":false,"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/A5090981549","display_name":"Stevan Ivkovi\u0107","orcid":null,"observed_orcids":[]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Stevan Ivkovi\u0107","raw_affiliation_strings":["1MC Maximus, Ni\u0161, Republic of Serbia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"1MC Maximus, Ni\u0161, Republic of Serbia","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5076488427","display_name":"Du\u0161an Ivkovi\u0107","orcid":"https://orcid.org/0009-0000-5433-5509","observed_orcids":["https://orcid.org/0009-0000-5433-5509"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Du\u0161an Ivkovi\u0107","raw_affiliation_strings":["1MC Maximus, Ni\u0161, Republic of Serbia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"1MC Maximus, Ni\u0161, Republic of Serbia","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5075918041","display_name":"Aleksandar Ivkovi\u0107","orcid":"https://orcid.org/0009-0004-6499-4734","observed_orcids":["https://orcid.org/0009-0004-6499-4734"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Aleksandar Ivkovi\u0107","raw_affiliation_strings":["1MC Maximus, Ni\u0161, Republic of Serbia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"1MC Maximus, Ni\u0161, Republic of Serbia","institution_ids":[]}]}],"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":"PA978","last_page":"PA978"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11636","display_name":"Artificial Intelligence in Healthcare and Education","score":0.8080999851226807,"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"}},"topics":[{"id":"https://openalex.org/T11636","display_name":"Artificial Intelligence in Healthcare and Education","score":0.8080999851226807,"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/T12422","display_name":"Radiomics and Machine Learning in Medical Imaging","score":0.06769999861717224,"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/T10862","display_name":"AI in cancer detection","score":0.05959999933838844,"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/artificial-intelligence","display_name":"artificial intelligence","score":0.8190000057220459},{"id":"https://openalex.org/keywords/lung-disease-diagnosis","display_name":"lung disease diagnosis","score":0.7369999885559082},{"id":"https://openalex.org/keywords/computed-tomography","display_name":"computed tomography","score":0.671999990940094},{"id":"https://openalex.org/keywords/pulmonary-nodules","display_name":"pulmonary nodules","score":0.8489999771118164},{"id":"https://openalex.org/keywords/interstitial-lung-disease","display_name":"interstitial lung disease","score":0.953000009059906},{"id":"https://openalex.org/keywords/diagnostic-accuracy","display_name":"diagnostic accuracy","score":0.5720000267028809},{"id":"https://openalex.org/keywords/interpretation-time","display_name":"interpretation time","score":0.9100000262260437},{"id":"https://openalex.org/keywords/inter-rater-reliability","display_name":"inter-rater reliability","score":0.9829999804496765},{"id":"https://openalex.org/keywords/missed-findings","display_name":"missed findings","score":0.6600000262260437},{"id":"https://openalex.org/keywords/radiology-workflow","display_name":"radiology workflow","score":0.6129999756813049}],"concepts":[{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.7129999995231628},{"id":"https://openalex.org/C3020132585","wikidata":"https://www.wikidata.org/wiki/Q2671652","display_name":"Diagnostic accuracy","level":2,"score":0.6194000244140625},{"id":"https://openalex.org/C2777543607","wikidata":"https://www.wikidata.org/wiki/Q1153419","display_name":"Interstitial lung disease","level":3,"score":0.6061000227928162},{"id":"https://openalex.org/C177212765","wikidata":"https://www.wikidata.org/wiki/Q627335","display_name":"Workflow","level":2,"score":0.560699999332428},{"id":"https://openalex.org/C126838900","wikidata":"https://www.wikidata.org/wiki/Q77604","display_name":"Radiology","level":1,"score":0.5546000003814697},{"id":"https://openalex.org/C2992779976","wikidata":"https://www.wikidata.org/wiki/Q3286546","display_name":"Pulmonary disease","level":2,"score":0.4909999966621399},{"id":"https://openalex.org/C43214815","wikidata":"https://www.wikidata.org/wiki/Q7310987","display_name":"Reliability (semiconductor)","level":3,"score":0.4255000054836273},{"id":"https://openalex.org/C534262118","wikidata":"https://www.wikidata.org/wiki/Q177719","display_name":"Medical diagnosis","level":2,"score":0.39070001244544983},{"id":"https://openalex.org/C2777714996","wikidata":"https://www.wikidata.org/wiki/Q7886","display_name":"Lung","level":2,"score":0.35920000076293945},{"id":"https://openalex.org/C31601959","wikidata":"https://www.wikidata.org/wiki/Q931309","display_name":"Medical imaging","level":2,"score":0.34369999170303345},{"id":"https://openalex.org/C82157600","wikidata":"https://www.wikidata.org/wiki/Q2671652","display_name":"Diagnostic test","level":2,"score":0.3434000015258789},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.34119999408721924},{"id":"https://openalex.org/C2776436953","wikidata":"https://www.wikidata.org/wiki/Q5163215","display_name":"Consistency (knowledge bases)","level":2,"score":0.3248000144958496},{"id":"https://openalex.org/C19527891","wikidata":"https://www.wikidata.org/wiki/Q1120908","display_name":"Medical physics","level":1,"score":0.32170000672340393},{"id":"https://openalex.org/C544519230","wikidata":"https://www.wikidata.org/wiki/Q32566","display_name":"Computed tomography","level":2,"score":0.31869998574256897},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3138999938964844},{"id":"https://openalex.org/C2983914783","wikidata":"https://www.wikidata.org/wiki/Q3286546","display_name":"Lung disease","level":3,"score":0.3043999969959259},{"id":"https://openalex.org/C2778341716","wikidata":"https://www.wikidata.org/wiki/Q2290446","display_name":"Idiopathic pulmonary fibrosis","level":3,"score":0.28610000014305115},{"id":"https://openalex.org/C527412718","wikidata":"https://www.wikidata.org/wiki/Q855395","display_name":"Interpretation (philosophy)","level":2,"score":0.28110000491142273},{"id":"https://openalex.org/C2776178081","wikidata":"https://www.wikidata.org/wiki/Q3286546","display_name":"Respiratory disease","level":3,"score":0.2727000117301941},{"id":"https://openalex.org/C3018822202","wikidata":"https://www.wikidata.org/wiki/Q1324077","display_name":"Patient data","level":2,"score":0.27250000834465027},{"id":"https://openalex.org/C3008058167","wikidata":"https://www.wikidata.org/wiki/Q84263196","display_name":"Coronavirus disease 2019 (COVID-19)","level":4,"score":0.2703999876976013},{"id":"https://openalex.org/C2779134260","wikidata":"https://www.wikidata.org/wiki/Q12136","display_name":"Disease","level":2,"score":0.26750001311302185},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.2630000114440918}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1183/13993003.congress-2025.pa978","doi":"https://doi.org/10.1183/13993003.congress-2025.pa978","is_oa":false,"landing_page_url":"https://doi.org/10.1183/13993003.congress-2025.pa978","pdf_url":null,"source":{"id":"https://openalex.org/S4210207896","display_name":"European Respiratory Journal","issn_l":"0903-1936","issn":["0903-1936","1399-3003"],"is_oa":false,"is_in_doaj":false,"is_core":true,"listed_in":["anvur-class-a","anvur-scientific","cwts-core","dongbi-a","doyens","jufo-3","ki-jl-3","medline","norway-2","poland-200","russia-white-list-1","vabb-shw"],"host_organization":"https://openalex.org/P4310317833","host_organization_name":"European Respiratory Society","host_organization_lineage":["https://openalex.org/P4310317833"],"host_organization_lineage_names":["European Respiratory Society"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Imaging","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/3","score":0.98580002784729,"display_name":"Good health and well-being"}],"study_designs":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W7220380349","https://openalex.org/W4406404189","https://openalex.org/W7220247796","https://openalex.org/W4406478186","https://openalex.org/W4417451188","https://openalex.org/W7216175450","https://openalex.org/W4380290629","https://openalex.org/W4417148756","https://openalex.org/W7008720434","https://openalex.org/W3215796869"],"abstract_inverted_index":{"The":[0,78,109],"rapid":[1],"advancement":[2],"of":[3,24,29,111,124,183,199],"artificial":[4],"intelligence":[5],"(AI)":[6],"has":[7,176],"opened":[8],"new":[9],"possibilities":[10],"for":[11,54,89],"improving":[12],"diagnostic":[13,38,64,115],"accuracy":[14],"and":[15,40,75,87,94,106,128,192],"efficiency":[16],"in":[17,69,121,132,159,168,189],"radiology.":[18],"This":[19],"study":[20],"evaluates":[21],"the":[22,63,122,177,197],"impact":[23],"AI":[25,58,79,96,112,175,201],"on":[26,33,83,101,148],"CT-based":[27,181],"diagnosis":[28,182],"pulmonary":[30,56,126,184],"diseases,":[31,185],"focusing":[32,100],"its":[34],"ability":[35],"to":[36,66,146,172,179],"enhance":[37],"precision":[39],"reduce":[41],"interpretation":[42,104],"time.":[43],"We":[44],"analyzed":[45],"data":[46],"from":[47],"5,446":[48],"patients":[49],"who":[50],"underwent":[51],"CT":[52],"scans":[53],"suspected":[55],"diseases.":[57],"algorithms":[59],"were":[60,98],"integrated":[61],"into":[62],"workflow":[65],"assist":[67],"radiologists":[68,145],"detecting":[70],"abnormalities,":[71],"including":[72],"nodules,":[73],"consolidations,":[74],"interstitial":[76,134],"patterns.":[77,137],"system":[80],"was":[81,140],"trained":[82],"a":[84,118,129],"diverse":[85],"dataset":[86],"validated":[88],"accuracy.":[90],"Diagnostic":[91],"outcomes":[92],"with":[93,117],"without":[95],"assistance":[97],"compared,":[99],"detection":[102,123],"rates,":[103],"time,":[105],"inter-rater":[107],"reliability.":[108],"use":[110],"significantly":[113],"improved":[114,153],"accuracy,":[116,190],"72%":[119],"increase":[120],"early-stage":[125],"nodules":[127],"68%":[130],"improvement":[131],"identifying":[133],"lung":[135],"disease":[136],"Interpretation":[138],"time":[139],"reduced":[141],"by":[142,154],"65%,":[143],"allowing":[144],"focus":[147],"complex":[149],"cases.":[150],"Inter-rater":[151],"reliability":[152],"78%,":[155],"demonstrating":[156],"greater":[157],"consistency":[158],"diagnoses.":[160],"Overall,":[161],"AI-assisted":[162],"diagnostics":[163],"achieved":[164],"an":[165],"80%":[166],"reduction":[167],"missed":[169],"findings":[170,195],"compared":[171],"traditional":[173],"methods.":[174],"potential":[178],"revolutionize":[180],"offering":[186],"substantial":[187],"improvements":[188],"efficiency,":[191],"consistency.":[193],"These":[194],"highlight":[196],"importance":[198],"integrating":[200]},"counts_by_year":[],"updated_date":"2026-11-02T09:45:03.842371","created_date":"2025-11-25T00:00:00"}