{"id":"https://openalex.org/W4417513140","doi":"https://doi.org/10.48550/arxiv.2505.06646","title":"Reproducing and Improving CheXNet: Deep Learning for Chest X-ray Disease Classification","display_name":"Reproducing and Improving CheXNet: Deep Learning for Chest X-ray Disease Classification","publication_year":2025,"publication_date":"2025-05-10","ids":{"openalex":"https://openalex.org/W4417513140","doi":"https://doi.org/10.48550/arxiv.2505.06646"},"language":"en","primary_location":{"id":"pmh:oai:arXiv.org:2505.06646","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2505.06646","pdf_url":"https://arxiv.org/pdf/2505.06646","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":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"type":"preprint","indexed_in":["arxiv","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2505.06646","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5119075440","display_name":"Daniel Strick","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Strick, Daniel J.","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5113225804","display_name":"Carlos Garc\u00eda","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Garcia, Carlos","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5057018549","display_name":"Anthony H. C. Huang","orcid":"https://orcid.org/0000-0002-5659-4579"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Huang, Anthony","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":null,"display_name":"Gardos, Thomas","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Gardos, Thomas","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":false,"primary_topic":{"id":"https://openalex.org/T11775","display_name":"COVID-19 diagnosis using AI","score":0.9035999774932861,"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"}},"topics":[{"id":"https://openalex.org/T11775","display_name":"COVID-19 diagnosis using AI","score":0.9035999774932861,"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":0.02199999988079071,"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/T14510","display_name":"Medical Imaging and Analysis","score":0.0142000000923872,"subfield":{"id":"https://openalex.org/subfields/2204","display_name":"Biomedical Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.761900007724762},{"id":"https://openalex.org/keywords/f1-score","display_name":"F1 score","score":0.4878999888896942},{"id":"https://openalex.org/keywords/baseline","display_name":"Baseline (sea)","score":0.42100000381469727},{"id":"https://openalex.org/keywords/field","display_name":"Field (mathematics)","score":0.4187000095844269},{"id":"https://openalex.org/keywords/clinical-practice","display_name":"Clinical Practice","score":0.39739999175071716},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3573000133037567}],"concepts":[{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.761900007724762},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7401999831199646},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5163999795913696},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5019000172615051},{"id":"https://openalex.org/C148524875","wikidata":"https://www.wikidata.org/wiki/Q6975395","display_name":"F1 score","level":2,"score":0.4878999888896942},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.4348999857902527},{"id":"https://openalex.org/C12725497","wikidata":"https://www.wikidata.org/wiki/Q810247","display_name":"Baseline (sea)","level":2,"score":0.42100000381469727},{"id":"https://openalex.org/C9652623","wikidata":"https://www.wikidata.org/wiki/Q190109","display_name":"Field (mathematics)","level":2,"score":0.4187000095844269},{"id":"https://openalex.org/C2779974597","wikidata":"https://www.wikidata.org/wiki/Q28448986","display_name":"Clinical Practice","level":2,"score":0.39739999175071716},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3573000133037567},{"id":"https://openalex.org/C31601959","wikidata":"https://www.wikidata.org/wiki/Q931309","display_name":"Medical imaging","level":2,"score":0.35659998655319214},{"id":"https://openalex.org/C2779134260","wikidata":"https://www.wikidata.org/wiki/Q12136","display_name":"Disease","level":2,"score":0.2913999855518341},{"id":"https://openalex.org/C110083411","wikidata":"https://www.wikidata.org/wiki/Q1744628","display_name":"Statistical classification","level":2,"score":0.258899986743927},{"id":"https://openalex.org/C19527891","wikidata":"https://www.wikidata.org/wiki/Q1120908","display_name":"Medical physics","level":1,"score":0.25600001215934753},{"id":"https://openalex.org/C75294576","wikidata":"https://www.wikidata.org/wiki/Q5165192","display_name":"Contextual image classification","level":3,"score":0.2506999969482422}],"mesh":[],"locations_count":3,"locations":[{"id":"pmh:oai:arXiv.org:2505.06646","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2505.06646","pdf_url":"https://arxiv.org/pdf/2505.06646","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":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},{"id":"pmh:doi:10.48550/arxiv.2505.06646","is_oa":true,"landing_page_url":null,"pdf_url":null,"source":{"id":"https://openalex.org/S4406922384","display_name":"Open MIND","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Article"},{"id":"doi:10.48550/arxiv.2505.06646","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2505.06646","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":"pmh:oai:arXiv.org:2505.06646","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2505.06646","pdf_url":"https://arxiv.org/pdf/2505.06646","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":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Deep":[0],"learning":[1],"for":[2,82],"radiologic":[3],"image":[4],"analysis":[5],"is":[6,15],"a":[7,19],"rapidly":[8],"growing":[9],"field":[10],"in":[11,22,87,113],"biomedical":[12],"research":[13],"and":[14,74,100],"likely":[16],"to":[17],"become":[18],"standard":[20],"practice":[21],"modern":[23],"medicine.":[24],"On":[25],"the":[26,39,71,114],"publicly":[27],"available":[28],"NIH":[29],"ChestX-ray14":[30],"dataset,":[31],"containing":[32],"X-ray":[33],"images":[34],"that":[35,60],"are":[36,79],"classified":[37],"by":[38],"presence":[40],"or":[41],"absence":[42],"of":[43,77,98,105],"14":[44,109],"different":[45],"diseases,":[46],"we":[47],"reproduced":[48],"an":[49,94,101],"algorithm":[50],"known":[51],"as":[52,54,56],"CheXNet,":[53],"well":[55],"explored":[57],"other":[58],"algorithms":[59],"outperform":[61],"CheXNet's":[62],"baseline":[63],"metrics.":[64],"Model":[65],"performance":[66],"was":[67],"primarily":[68],"evaluated":[69],"using":[70],"F1":[72,103],"score":[73,97,104],"AUC-ROC,":[75],"both":[76],"which":[78],"critical":[80],"metrics":[81],"imbalanced,":[83],"multi-label":[84],"classification":[85],"tasks":[86],"medical":[88],"imaging.":[89],"The":[90],"best":[91],"model":[92],"achieved":[93],"average":[95,102],"AUC-ROC":[96],"0.85":[99],"0.39":[106],"across":[107],"all":[108],"disease":[110],"classifications":[111],"present":[112],"dataset.":[115]},"counts_by_year":[],"updated_date":"2026-08-05T07:39:15.569665","created_date":"2025-10-10T00:00:00"}