{"id":"https://openalex.org/W7140130833","doi":"https://doi.org/10.3390/s26061998","title":"Strategies for Class-Imbalanced Learning in Multi-Sensor Medical Imaging","display_name":"Strategies for Class-Imbalanced Learning in Multi-Sensor Medical Imaging","publication_year":2026,"publication_date":"2026-03-23","ids":{"openalex":"https://openalex.org/W7140130833","doi":"https://doi.org/10.3390/s26061998","pmid":"https://pubmed.ncbi.nlm.nih.gov/41902166"},"language":"en","primary_location":{"id":"doi:10.3390/s26061998","doi":"https://doi.org/10.3390/s26061998","is_oa":true,"landing_page_url":"https://doi.org/10.3390/s26061998","pdf_url":"https://www.mdpi.com/1424-8220/26/6/1998/pdf?version=1774270723","source":{"id":"https://openalex.org/S101949793","display_name":"Sensors","issn_l":"1424-8220","issn":["1424-8220"],"is_oa":true,"is_in_doaj":true,"is_core":true,"listed_in":["anvur-scientific","cwts-core","doaj","jufo-1","medline","norway-1","poland-100","russia-white-list-1","vabb-shw"],"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Sensors","raw_type":"journal-article"},"volume":null,"type":"article","indexed_in":["crossref","doaj","pubmed"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.mdpi.com/1424-8220/26/6/1998/pdf?version=1774270723","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5130408422","display_name":"Da Zhou","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]},{"id":"https://openalex.org/I4210141942","display_name":"Peking University Third Hospital","ror":"https://ror.org/04wwqze12","country_code":"CN","type":"healthcare","lineage":["https://openalex.org/I4210141942"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Da Zhou","raw_affiliation_strings":["Beijing Key Laboratory of Intelligent Neuromodulation and Brain Disorder Treatment, Peking University Third Hospital, Beijing 100191, China","Department of Biophysics, School of Basic Medical Sciences, Peking University, Beijing 100191, China","Key Laboratory for Neuroscience, Ministry of Education and National Health Commission, Beijing 100191, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Beijing Key Laboratory of Intelligent Neuromodulation and Brain Disorder Treatment, Peking University Third Hospital, Beijing 100191, China","institution_ids":["https://openalex.org/I4210141942"]},{"raw_affiliation_string":"Department of Biophysics, School of Basic Medical Sciences, Peking University, Beijing 100191, China","institution_ids":["https://openalex.org/I20231570"]},{"raw_affiliation_string":"Key Laboratory for Neuroscience, Ministry of Education and National Health Commission, Beijing 100191, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5130399964","display_name":"Song Gao","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]},{"id":"https://openalex.org/I4210141942","display_name":"Peking University Third Hospital","ror":"https://ror.org/04wwqze12","country_code":"CN","type":"healthcare","lineage":["https://openalex.org/I4210141942"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Song Gao","raw_affiliation_strings":["Beijing Key Laboratory of Intelligent Neuromodulation and Brain Disorder Treatment, Peking University Third Hospital, Beijing 100191, China","Institute of Medical Technology, Peking University Health Science Center, Beijing 100191, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Beijing Key Laboratory of Intelligent Neuromodulation and Brain Disorder Treatment, Peking University Third Hospital, Beijing 100191, China","institution_ids":["https://openalex.org/I4210141942"]},{"raw_affiliation_string":"Institute of Medical Technology, Peking University Health Science Center, Beijing 100191, China","institution_ids":["https://openalex.org/I20231570"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5076754895","display_name":"Xinrui Huang","orcid":"https://orcid.org/0000-0002-7709-1137","observed_orcids":["https://orcid.org/0000-0002-7709-1137"]},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]},{"id":"https://openalex.org/I4210141942","display_name":"Peking University Third Hospital","ror":"https://ror.org/04wwqze12","country_code":"CN","type":"healthcare","lineage":["https://openalex.org/I4210141942"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Xinrui Huang","raw_affiliation_strings":["Beijing Key Laboratory of Intelligent Neuromodulation and Brain Disorder Treatment, Peking University Third Hospital, Beijing 100191, China","Department of Biophysics, School of Basic Medical Sciences, Peking University, Beijing 100191, China","Key Laboratory for Neuroscience, Ministry of Education and National Health Commission, Beijing 100191, China"],"raw_orcid":"https://orcid.org/0000-0002-7709-1137","affiliations":[{"raw_affiliation_string":"Beijing Key Laboratory of Intelligent Neuromodulation and Brain Disorder Treatment, Peking University Third Hospital, Beijing 100191, China","institution_ids":["https://openalex.org/I4210141942"]},{"raw_affiliation_string":"Department of Biophysics, School of Basic Medical Sciences, Peking University, Beijing 100191, China","institution_ids":["https://openalex.org/I20231570"]},{"raw_affiliation_string":"Key Laboratory for Neuroscience, Ministry of Education and National Health Commission, Beijing 100191, China","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5076754895","https://openalex.org/A5130399964"],"corresponding_institution_ids":["https://openalex.org/I20231570","https://openalex.org/I4210141942"],"apc_list":{"value":2600,"currency":"CHF","value_usd":3137},"apc_paid":{"value":2600,"currency":"CHF","value_usd":3137},"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.17846068,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"26","issue":"6","first_page":"1998","last_page":"1998"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11652","display_name":"Imbalanced Data Classification Techniques","score":0.9779999852180481,"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/T11652","display_name":"Imbalanced Data Classification Techniques","score":0.9779999852180481,"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":0.00989999994635582,"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/T10052","display_name":"Medical Image Segmentation Techniques","score":0.0017999999690800905,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/class-imbalance","display_name":"class imbalance","score":0.9649999737739563},{"id":"https://openalex.org/keywords/multimodal-fusion","display_name":"multimodal fusion","score":0.7540000081062317},{"id":"https://openalex.org/keywords/rare-disease-diagnosis","display_name":"rare disease diagnosis","score":0.7009999752044678},{"id":"https://openalex.org/keywords/transfer-learning","display_name":"transfer learning","score":0.9919999837875366},{"id":"https://openalex.org/keywords/ensemble-methods","display_name":"ensemble methods","score":0.9570000171661377},{"id":"https://openalex.org/keywords/early-fusion","display_name":"feature-level fusion","score":0.8330000042915344},{"id":"https://openalex.org/keywords/decision-level-fusion","display_name":"decision fusion","score":0.9990000128746033},{"id":"https://openalex.org/keywords/federated-learning","display_name":"federated learning","score":0.7450000047683716},{"id":"https://openalex.org/keywords/explainable-ai","display_name":"explainable AI","score":0.9779999852180481},{"id":"https://openalex.org/keywords/fda-compliance","display_name":"FDA compliance","score":0.5559999942779541}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.656000018119812},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.632099986076355},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.525600016117096},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5065000057220459},{"id":"https://openalex.org/C31601959","wikidata":"https://www.wikidata.org/wiki/Q931309","display_name":"Medical imaging","level":2,"score":0.4961000084877014},{"id":"https://openalex.org/C2777212361","wikidata":"https://www.wikidata.org/wiki/Q5127848","display_name":"Class (philosophy)","level":2,"score":0.4657999873161316},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.461899995803833},{"id":"https://openalex.org/C2776035091","wikidata":"https://www.wikidata.org/wiki/Q7928819","display_name":"Viewpoints","level":2,"score":0.38940000534057617},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.3499000072479248},{"id":"https://openalex.org/C150921843","wikidata":"https://www.wikidata.org/wiki/Q1170431","display_name":"Resampling","level":2,"score":0.3495999872684479},{"id":"https://openalex.org/C155911762","wikidata":"https://www.wikidata.org/wiki/Q422321","display_name":"Blueprint","level":2,"score":0.34139999747276306},{"id":"https://openalex.org/C33954974","wikidata":"https://www.wikidata.org/wiki/Q486494","display_name":"Sensor fusion","level":2,"score":0.33469998836517334},{"id":"https://openalex.org/C14036430","wikidata":"https://www.wikidata.org/wiki/Q3736076","display_name":"Function (biology)","level":2,"score":0.32199999690055847},{"id":"https://openalex.org/C100660578","wikidata":"https://www.wikidata.org/wiki/Q18733","display_name":"Recall","level":2,"score":0.3133000135421753},{"id":"https://openalex.org/C109747225","wikidata":"https://www.wikidata.org/wiki/Q815758","display_name":"Scarcity","level":2,"score":0.3086000084877014},{"id":"https://openalex.org/C75684735","wikidata":"https://www.wikidata.org/wiki/Q858810","display_name":"Big data","level":2,"score":0.3003000020980835},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.27810001373291016},{"id":"https://openalex.org/C150899416","wikidata":"https://www.wikidata.org/wiki/Q1820378","display_name":"Transfer of learning","level":2,"score":0.26339998841285706}],"mesh":[{"descriptor_ui":"D000069550","descriptor_name":"Machine Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D000069550","descriptor_name":"Machine Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D000069550","descriptor_name":"Machine Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D000069550","descriptor_name":"Machine Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D000069550","descriptor_name":"Machine Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D000069550","descriptor_name":"Machine Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D000098407","descriptor_name":"Federated Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000098407","descriptor_name":"Federated Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000098407","descriptor_name":"Federated Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000465","descriptor_name":"Algorithms","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000465","descriptor_name":"Algorithms","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000465","descriptor_name":"Algorithms","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000465","descriptor_name":"Algorithms","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000465","descriptor_name":"Algorithms","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000465","descriptor_name":"Algorithms","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D001185","descriptor_name":"Artificial Intelligence","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D001185","descriptor_name":"Artificial Intelligence","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D001185","descriptor_name":"Artificial Intelligence","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D003952","descriptor_name":"Diagnostic Imaging","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":true},{"descriptor_ui":"D003952","descriptor_name":"Diagnostic Imaging","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":true},{"descriptor_ui":"D003952","descriptor_name":"Diagnostic Imaging","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":true},{"descriptor_ui":"D003952","descriptor_name":"Diagnostic Imaging","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":true},{"descriptor_ui":"D003952","descriptor_name":"Diagnostic Imaging","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":true},{"descriptor_ui":"D003952","descriptor_name":"Diagnostic Imaging","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":true},{"descriptor_ui":"D006801","descriptor_name":"Humans","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D006801","descriptor_name":"Humans","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D006801","descriptor_name":"Humans","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D006801","descriptor_name":"Humans","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D006801","descriptor_name":"Humans","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D006801","descriptor_name":"Humans","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D008279","descriptor_name":"Magnetic Resonance Imaging","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D008279","descriptor_name":"Magnetic Resonance Imaging","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D008279","descriptor_name":"Magnetic Resonance Imaging","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D008279","descriptor_name":"Magnetic Resonance Imaging","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D008279","descriptor_name":"Magnetic Resonance Imaging","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D008279","descriptor_name":"Magnetic Resonance Imaging","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D014057","descriptor_name":"Tomography, X-Ray Computed","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D014057","descriptor_name":"Tomography, X-Ray Computed","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D014057","descriptor_name":"Tomography, X-Ray Computed","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D014057","descriptor_name":"Tomography, X-Ray Computed","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D014057","descriptor_name":"Tomography, X-Ray Computed","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D014057","descriptor_name":"Tomography, X-Ray Computed","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false}],"locations_count":4,"locations":[{"id":"doi:10.3390/s26061998","doi":"https://doi.org/10.3390/s26061998","is_oa":true,"landing_page_url":"https://doi.org/10.3390/s26061998","pdf_url":"https://www.mdpi.com/1424-8220/26/6/1998/pdf?version=1774270723","source":{"id":"https://openalex.org/S101949793","display_name":"Sensors","issn_l":"1424-8220","issn":["1424-8220"],"is_oa":true,"is_in_doaj":true,"is_core":true,"listed_in":["anvur-scientific","cwts-core","doaj","jufo-1","medline","norway-1","poland-100","russia-white-list-1","vabb-shw"],"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Sensors","raw_type":"journal-article"},{"id":"pmid:41902166","doi":null,"is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/41902166","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Sensors (Basel, Switzerland)","raw_type":"Journal Article"},{"id":"pmh:oai:pubmedcentral.nih.gov:13029843","doi":null,"is_oa":true,"landing_page_url":"https://pmc.ncbi.nlm.nih.gov/articles/PMC13029843/","pdf_url":"https://pmc.ncbi.nlm.nih.gov/articles/PMC13029843/pdf/sensors-26-01998.pdf","source":{"id":"https://openalex.org/S2764455111","display_name":"PubMed Central","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"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":"Sensors (Basel)","raw_type":"Text"},{"id":"pmh:oai:doaj.org/article:e2d0d304c4e248d3b2861c55a00a7044","doi":null,"is_oa":true,"landing_page_url":"https://doaj.org/article/e2d0d304c4e248d3b2861c55a00a7044","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Sensors, Vol 26, Iss 6, p 1998 (2026)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.3390/s26061998","doi":"https://doi.org/10.3390/s26061998","is_oa":true,"landing_page_url":"https://doi.org/10.3390/s26061998","pdf_url":"https://www.mdpi.com/1424-8220/26/6/1998/pdf?version=1774270723","source":{"id":"https://openalex.org/S101949793","display_name":"Sensors","issn_l":"1424-8220","issn":["1424-8220"],"is_oa":true,"is_in_doaj":true,"is_core":true,"listed_in":["anvur-scientific","cwts-core","doaj","jufo-1","medline","norway-1","poland-100","russia-white-list-1","vabb-shw"],"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Sensors","raw_type":"journal-article"},"sustainable_development_goals":[{"display_name":"Good health and well-being","id":"https://metadata.un.org/sdg/3","score":0.6240000128746033},{"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10","score":0.4074000120162964}],"sustainable_development_goals_aurora":[{"display_name":"Peace, justice, and strong institutions","id":"https://metadata.un.org/sdg/16","score":0.4901060461997986}],"study_designs":[],"awards":[{"id":"https://openalex.org/G3882533929","display_name":null,"funder_award_id":"82572374","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320324787","display_name":"Peking University","ror":"https://ror.org/02v51f717"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W7140130833.pdf","grobid_xml":"https://content.openalex.org/works/W7140130833.grobid-xml"},"referenced_works_count":46,"referenced_works":["https://openalex.org/W91904439","https://openalex.org/W1593438720","https://openalex.org/W1993220166","https://openalex.org/W2118978333","https://openalex.org/W2148143831","https://openalex.org/W2331050695","https://openalex.org/W2345010043","https://openalex.org/W2767106145","https://openalex.org/W2900954917","https://openalex.org/W2908201961","https://openalex.org/W2911153558","https://openalex.org/W2995327724","https://openalex.org/W2996480032","https://openalex.org/W3030278180","https://openalex.org/W3096831136","https://openalex.org/W3114304902","https://openalex.org/W3131657814","https://openalex.org/W3138892710","https://openalex.org/W3158264953","https://openalex.org/W3160412534","https://openalex.org/W3184080322","https://openalex.org/W3211522713","https://openalex.org/W4200481904","https://openalex.org/W4292877297","https://openalex.org/W4304811942","https://openalex.org/W4306936963","https://openalex.org/W4379057644","https://openalex.org/W4382371436","https://openalex.org/W4387211769","https://openalex.org/W4387728269","https://openalex.org/W4389074726","https://openalex.org/W4391743499","https://openalex.org/W4391768987","https://openalex.org/W4391952659","https://openalex.org/W4393866995","https://openalex.org/W4394912784","https://openalex.org/W4396569549","https://openalex.org/W4396773505","https://openalex.org/W4399014789","https://openalex.org/W4400387343","https://openalex.org/W4403947618","https://openalex.org/W4405215306","https://openalex.org/W4406560469","https://openalex.org/W4408951610","https://openalex.org/W4410698373","https://openalex.org/W4417169499"],"related_works":[],"abstract_inverted_index":{"This":[0,55],"narrative":[1],"critical":[2,21],"review":[3,56],"addresses":[4],"class":[5,65,170],"imbalance":[6,177],"in":[7,174,191],"medical":[8,193],"imaging,":[9],"particularly":[10],"within":[11],"the":[12],"context":[13],"of":[14,31,61,189],"multi-sensor":[15,98,141,192],"and":[16,39,82,90,101,126,146,155],"multi-modal":[17],"environments,":[18],"poses":[19],"a":[20,42,58,113,150],"challenge":[22],"to":[23,45,63,202],"developing":[24],"reliable":[25],"AI":[26],"diagnostic":[27,158],"systems.":[28],"The":[29],"integration":[30],"heterogeneous":[32],"data":[33,47,78],"from":[34,200],"sources":[35],"like":[36,74],"CT,":[37],"MRI,":[38],"PET":[40],"presents":[41],"unique":[43],"opportunity":[44],"address":[46],"scarcity":[48],"for":[49,76,109],"rare":[50],"conditions":[51],"through":[52],"fusion":[53,100,103,142],"techniques.":[54],"provides":[57],"structured":[59],"analysis":[60],"strategies":[62,166,183],"tackle":[64],"imbalance,":[66],"categorizing":[67],"them":[68],"into":[69],"data-centric":[70,165],"(e.g.,":[71,84,129],"advanced":[72],"resampling":[73],"SMOTE-ENC":[75],"mixed":[77],"types,":[79],"GAN-based":[80],"synthesis)":[81],"model-centric":[83,182],"loss":[85],"function":[86],"engineering,":[87],"transfer":[88],"learning,":[89,145],"ensemble":[91],"methods)":[92],"approaches.":[93],"Crucially,":[94],"we":[95,132],"highlight":[96],"how":[97],"feature":[99],"decision-level":[102],"paradigms":[104],"can":[105,167],"inherently":[106],"enrich":[107],"representations":[108],"minority":[110,169],"classes,":[111],"offering":[112],"powerful":[114],"frontier":[115],"beyond":[116],"single-modality":[117],"learning.":[118],"We":[119],"evaluate":[120],"each":[121],"method's":[122],"merits,":[123],"clinical":[124],"viability,":[125],"compliance":[127],"considerations":[128],"FDA).":[130],"Finally,":[131],"identify":[133],"emerging":[134],"trends":[135],"where":[136],"imbalance-aware":[137],"learning":[138],"synergizes":[139],"with":[140,176,196],"frameworks,":[143],"federated":[144],"explainable":[147],"AI,":[148],"charting":[149],"roadmap":[151],"toward":[152],"robust,":[153],"equitable,":[154],"clinically":[156],"deployable":[157],"tools.":[159],"Our":[160],"quantitative":[161],"synthesis":[162],"shows":[163],"that":[164],"improve":[168],"recall":[171],"by":[172],"12-35%":[173],"datasets":[175],"ratios":[178],"(majority:minority)":[179],"\u226510:1,":[180],"while":[181],"achieve":[184],"an":[185],"average":[186],"AUC":[187],"improvement":[188],"0.08-0.21":[190],"imaging":[194],"tasks":[195],"sample":[197],"sizes":[198],"ranging":[199],"50":[201],"50,000.":[203]},"counts_by_year":[],"updated_date":"2026-10-14T16:39:01.820549","created_date":"2026-03-24T00:00:00"}