{"id":"https://openalex.org/W3087117346","doi":"https://doi.org/10.1109/tbme.2021.3054248","title":"Applying a Random Projection Algorithm to Optimize Machine Learning Model for Breast Lesion Classification","display_name":"Applying a Random Projection Algorithm to Optimize Machine Learning Model for Breast Lesion Classification","publication_year":2021,"publication_date":"2021-01-25","ids":{"openalex":"https://openalex.org/W3087117346","doi":"https://doi.org/10.1109/tbme.2021.3054248","mag":"3087117346","pmid":"https://pubmed.ncbi.nlm.nih.gov/33493108"},"language":"en","primary_location":{"id":"doi:10.1109/tbme.2021.3054248","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tbme.2021.3054248","pdf_url":null,"source":{"id":"https://openalex.org/S5240358","display_name":"IEEE Transactions on Biomedical Engineering","issn_l":"0018-9294","issn":["0018-9294","1558-2531"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Biomedical Engineering","raw_type":"journal-article"},"type":"article","indexed_in":["arxiv","crossref","pubmed"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2009.09937","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5044959175","display_name":"Morteza Heidari","orcid":"https://orcid.org/0000-0003-0922-787X"},"institutions":[{"id":"https://openalex.org/I8692664","display_name":"University of Oklahoma","ror":"https://ror.org/02aqsxs83","country_code":"US","type":"education","lineage":["https://openalex.org/I8692664"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Morteza Heidari","raw_affiliation_strings":["School of Electrical and Computer Engineering, University of Oklahoma, Norman, OK, USA"],"raw_orcid":"https://orcid.org/0000-0003-0922-787X","affiliations":[{"raw_affiliation_string":"School of Electrical and Computer Engineering, University of Oklahoma, Norman, OK, USA","institution_ids":["https://openalex.org/I8692664"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5048317896","display_name":"S. Lakshmivarahan","orcid":"https://orcid.org/0000-0001-5113-9166"},"institutions":[{"id":"https://openalex.org/I8692664","display_name":"University of Oklahoma","ror":"https://ror.org/02aqsxs83","country_code":"US","type":"education","lineage":["https://openalex.org/I8692664"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Sivaramakrishnan Lakshmivarahan","raw_affiliation_strings":["School of Computer Science, University of Oklahoma, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Science, University of Oklahoma, USA","institution_ids":["https://openalex.org/I8692664"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5003646582","display_name":"Seyedehnafiseh Mirniaharikandehei","orcid":"https://orcid.org/0000-0002-1070-4517"},"institutions":[{"id":"https://openalex.org/I8692664","display_name":"University of Oklahoma","ror":"https://ror.org/02aqsxs83","country_code":"US","type":"education","lineage":["https://openalex.org/I8692664"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Seyedehnafiseh Mirniaharikandehei","raw_affiliation_strings":["School of Electrical and Computer Engineering, University of Oklahoma, USA"],"raw_orcid":"https://orcid.org/0000-0002-1070-4517","affiliations":[{"raw_affiliation_string":"School of Electrical and Computer Engineering, University of Oklahoma, USA","institution_ids":["https://openalex.org/I8692664"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5037175940","display_name":"Gopichandh Danala","orcid":"https://orcid.org/0000-0001-6857-9408"},"institutions":[{"id":"https://openalex.org/I8692664","display_name":"University of Oklahoma","ror":"https://ror.org/02aqsxs83","country_code":"US","type":"education","lineage":["https://openalex.org/I8692664"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Gopichandh Danala","raw_affiliation_strings":["School of Electrical and Computer Engineering, University of Oklahoma, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Electrical and Computer Engineering, University of Oklahoma, USA","institution_ids":["https://openalex.org/I8692664"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5089293830","display_name":"Sai Kiran Maryada","orcid":"https://orcid.org/0000-0003-1982-1012"},"institutions":[{"id":"https://openalex.org/I8692664","display_name":"University of Oklahoma","ror":"https://ror.org/02aqsxs83","country_code":"US","type":"education","lineage":["https://openalex.org/I8692664"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Sai Kiran R. Maryada","raw_affiliation_strings":["School of Computer Science, University of Oklahoma, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Science, University of Oklahoma, USA","institution_ids":["https://openalex.org/I8692664"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100410286","display_name":"Hong Liu","orcid":"https://orcid.org/0000-0002-0896-8409"},"institutions":[{"id":"https://openalex.org/I8692664","display_name":"University of Oklahoma","ror":"https://ror.org/02aqsxs83","country_code":"US","type":"education","lineage":["https://openalex.org/I8692664"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Hong Liu","raw_affiliation_strings":["School of Electrical and Computer Engineering, University of Oklahoma, USA"],"raw_orcid":"https://orcid.org/0000-0002-0896-8409","affiliations":[{"raw_affiliation_string":"School of Electrical and Computer Engineering, University of Oklahoma, USA","institution_ids":["https://openalex.org/I8692664"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5045998635","display_name":"Bin Zheng","orcid":"https://orcid.org/0000-0002-7682-6648"},"institutions":[{"id":"https://openalex.org/I8692664","display_name":"University of Oklahoma","ror":"https://ror.org/02aqsxs83","country_code":"US","type":"education","lineage":["https://openalex.org/I8692664"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Bin Zheng","raw_affiliation_strings":["School of Electrical and Computer Engineering, University of Oklahoma, USA"],"raw_orcid":"https://orcid.org/0000-0002-7682-6648","affiliations":[{"raw_affiliation_string":"School of Electrical and Computer Engineering, University of Oklahoma, USA","institution_ids":["https://openalex.org/I8692664"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":7,"corresponding_author_ids":["https://openalex.org/A5044959175"],"corresponding_institution_ids":["https://openalex.org/I8692664"],"apc_list":null,"apc_paid":null,"fwci":3.4981,"has_fulltext":false,"cited_by_count":33,"citation_normalized_percentile":{"value":0.93597444,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":"68","issue":"9","first_page":"2764","last_page":"2775"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10862","display_name":"AI in cancer detection","score":0.949400007724762,"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/T10862","display_name":"AI in cancer detection","score":0.949400007724762,"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/T12702","display_name":"Brain Tumor Detection and Classification","score":0.004900000058114529,"subfield":{"id":"https://openalex.org/subfields/2808","display_name":"Neurology"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T11396","display_name":"Artificial Intelligence in Healthcare","score":0.004600000102072954,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7295671701431274},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.6604865789413452},{"id":"https://openalex.org/keywords/cad","display_name":"CAD","score":0.6358886361122131},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6280028820037842},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.60427325963974},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5994012951850891},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.5702149271965027},{"id":"https://openalex.org/keywords/random-forest","display_name":"Random forest","score":0.559048593044281},{"id":"https://openalex.org/keywords/projection","display_name":"Projection (relational algebra)","score":0.5114449262619019},{"id":"https://openalex.org/keywords/dimensionality-reduction","display_name":"Dimensionality reduction","score":0.5077996850013733},{"id":"https://openalex.org/keywords/feature-vector","display_name":"Feature vector","score":0.48180192708969116},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.42473211884498596}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7295671701431274},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.6604865789413452},{"id":"https://openalex.org/C194789388","wikidata":"https://www.wikidata.org/wiki/Q17855283","display_name":"CAD","level":2,"score":0.6358886361122131},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6280028820037842},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.60427325963974},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5994012951850891},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.5702149271965027},{"id":"https://openalex.org/C169258074","wikidata":"https://www.wikidata.org/wiki/Q245748","display_name":"Random forest","level":2,"score":0.559048593044281},{"id":"https://openalex.org/C57493831","wikidata":"https://www.wikidata.org/wiki/Q3134666","display_name":"Projection (relational algebra)","level":2,"score":0.5114449262619019},{"id":"https://openalex.org/C70518039","wikidata":"https://www.wikidata.org/wiki/Q16000077","display_name":"Dimensionality reduction","level":2,"score":0.5077996850013733},{"id":"https://openalex.org/C83665646","wikidata":"https://www.wikidata.org/wiki/Q42139305","display_name":"Feature vector","level":2,"score":0.48180192708969116},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.42473211884498596},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C199639397","wikidata":"https://www.wikidata.org/wiki/Q1788588","display_name":"Engineering drawing","level":1,"score":0.0}],"mesh":[{"descriptor_ui":"D000069550","descriptor_name":"Machine Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000069550","descriptor_name":"Machine Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000069550","descriptor_name":"Machine 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":"D001943","descriptor_name":"Breast Neoplasms","qualifier_ui":"Q000000981","qualifier_name":"diagnostic imaging","is_major_topic":true},{"descriptor_ui":"D001943","descriptor_name":"Breast Neoplasms","qualifier_ui":"Q000000981","qualifier_name":"diagnostic imaging","is_major_topic":true},{"descriptor_ui":"D001943","descriptor_name":"Breast Neoplasms","qualifier_ui":"Q000000981","qualifier_name":"diagnostic imaging","is_major_topic":true},{"descriptor_ui":"D005260","descriptor_name":"Female","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D005260","descriptor_name":"Female","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D005260","descriptor_name":"Female","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":"D008327","descriptor_name":"Mammography","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D008327","descriptor_name":"Mammography","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D008327","descriptor_name":"Mammography","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D011857","descriptor_name":"Radiographic Image Interpretation, Computer-Assisted","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D011857","descriptor_name":"Radiographic Image Interpretation, Computer-Assisted","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D011857","descriptor_name":"Radiographic Image Interpretation, Computer-Assisted","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D012189","descriptor_name":"Retrospective Studies","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D012189","descriptor_name":"Retrospective Studies","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D012189","descriptor_name":"Retrospective Studies","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D060388","descriptor_name":"Support Vector Machine","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D060388","descriptor_name":"Support Vector Machine","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D060388","descriptor_name":"Support Vector Machine","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false}],"locations_count":4,"locations":[{"id":"doi:10.1109/tbme.2021.3054248","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tbme.2021.3054248","pdf_url":null,"source":{"id":"https://openalex.org/S5240358","display_name":"IEEE Transactions on Biomedical Engineering","issn_l":"0018-9294","issn":["0018-9294","1558-2531"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Biomedical Engineering","raw_type":"journal-article"},{"id":"pmid:33493108","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/33493108","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,"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":"IEEE transactions on bio-medical engineering","raw_type":null},{"id":"pmh:oai:arXiv.org:2009.09937","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2009.09937","pdf_url":"https://arxiv.org/pdf/2009.09937","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"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:oai:pubmedcentral.nih.gov:8310536","is_oa":true,"landing_page_url":"https://www.ncbi.nlm.nih.gov/pmc/articles/8310536","pdf_url":null,"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,"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":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Trans Biomed Eng","raw_type":"Text"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2009.09937","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2009.09937","pdf_url":"https://arxiv.org/pdf/2009.09937","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"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":[{"id":"https://openalex.org/G2361291814","display_name":null,"funder_award_id":"R01-CA197150","funder_id":"https://openalex.org/F4320310678","funder_display_name":"Center for Strategic Scientific Initiatives, National Cancer Institute"}],"funders":[{"id":"https://openalex.org/F4320306080","display_name":"Foundation for the National Institutes of Health","ror":"https://ror.org/00k86s890"},{"id":"https://openalex.org/F4320310678","display_name":"Center for Strategic Scientific Initiatives, National Cancer Institute","ror":"https://ror.org/040gcmg81"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":40,"referenced_works":["https://openalex.org/W1974001716","https://openalex.org/W1974636983","https://openalex.org/W1980738513","https://openalex.org/W2003304826","https://openalex.org/W2016771288","https://openalex.org/W2041836310","https://openalex.org/W2044465660","https://openalex.org/W2070127246","https://openalex.org/W2074072216","https://openalex.org/W2085391848","https://openalex.org/W2104624965","https://openalex.org/W2105184687","https://openalex.org/W2114609025","https://openalex.org/W2117395697","https://openalex.org/W2134916573","https://openalex.org/W2165533158","https://openalex.org/W2248644291","https://openalex.org/W2280515386","https://openalex.org/W2287342701","https://openalex.org/W2301541953","https://openalex.org/W2339824777","https://openalex.org/W2471685161","https://openalex.org/W2493080670","https://openalex.org/W2557798449","https://openalex.org/W2582278192","https://openalex.org/W2606915180","https://openalex.org/W2775577467","https://openalex.org/W2787248994","https://openalex.org/W2801188218","https://openalex.org/W2890945786","https://openalex.org/W2894461463","https://openalex.org/W2958857749","https://openalex.org/W2965758364","https://openalex.org/W2969717447","https://openalex.org/W2979608765","https://openalex.org/W2980406415","https://openalex.org/W2990272570","https://openalex.org/W3036314019","https://openalex.org/W4250954493","https://openalex.org/W4285719527"],"related_works":["https://openalex.org/W2334610590","https://openalex.org/W3193043704","https://openalex.org/W4386259002","https://openalex.org/W1546989560","https://openalex.org/W2320366403","https://openalex.org/W3204197061","https://openalex.org/W3171520305","https://openalex.org/W1980222719","https://openalex.org/W6057950","https://openalex.org/W1499137908"],"abstract_inverted_index":{"OBJECTIVE:":[0],"Since":[1],"computer-aided":[2],"diagnosis":[3],"(CAD)":[4],"schemes":[5,245],"of":[6,13,20,38,45,68,81,130,151,162,165,211],"medical":[7],"images":[8],"usually":[9],"computes":[10],"large":[11,62],"number":[12],"image":[14],"features,":[15],"which":[16,84],"creates":[17],"a":[18,24,47,75,142,148,173,198,223,239],"challenge":[19],"how":[21],"to":[22,30,42,52,103,127,226,242],"identify":[23],"small":[25],"and":[26,65,92,107,139,190,231,249],"optimal":[27,55,228],"feature":[28,56,63,121,229],"vector":[29,57,114],"build":[31,53],"robust":[32,250],"machine":[33,69,115],"learning":[34,70],"models,":[35],"the":[36,59,166,183,206],"objective":[37],"this":[39],"study":[40,218,237],"is":[41,100,177,222],"investigate":[43],"feasibility":[44],"applying":[46],"random":[48],"projection":[49],"algorithm":[50],"(RPA)":[51],"an":[54],"from":[58],"initially":[60,108],"CAD-generated":[61],"pool":[64],"improve":[66,232],"performance":[67,204],"model.":[71],"METHODS:":[72],"We":[73],"assemble":[74],"retrospective":[76],"dataset":[77],"involving":[78],"1,487":[79],"cases":[80,86],"mammograms":[82],"in":[83],"644":[85],"have":[87,94],"confirmed":[88],"malignant":[89],"mass":[90,105,154,168],"lesions":[91,131],"843":[93],"benign":[95],"lesions.":[96],"A":[97],"CAD":[98,244],"scheme":[99],"first":[101],"applied":[102],"segment":[104],"regions":[106],"compute":[109],"181":[110],"features.":[111],"Then,":[112],"support":[113],"(SVM)":[116],"models":[117,136],"embedded":[118,194],"with":[119,182,195,205,246],"several":[120],"dimensionality":[122],"reduction":[123],"methods":[124],"are":[125,137],"built":[126],"predict":[128],"likelihood":[129,149,175],"being":[132],"malignant.":[133],"All":[134],"SVM":[135,146,193,233],"trained":[138],"tested":[140],"using":[141],"leave-one-case-out":[143],"cross-validation":[144],"method.":[145],"generates":[147],"score":[150,176],"each":[152],"segmented":[153],"region":[155],"depicting":[156,169],"on":[157,170],"one-view":[158],"mammogram.":[159],"By":[160],"fusion":[161],"two":[163],"scores":[164],"same":[167],"two-view":[171],"mammograms,":[172],"case-based":[174,201],"also":[178],"evaluated.":[179],"RESULTS:":[180],"Comparing":[181],"principle":[184],"component":[185],"analyses,":[186],"nonnegative":[187],"matrix":[188],"factorization,":[189],"Chi-squared":[191],"methods,":[192],"RPA":[196,221],"yielded":[197],"significantly":[199,247],"higher":[200,248],"lesion":[202],"classification":[203],"area":[207],"under":[208],"ROC":[209],"curve":[210],"0.84":[212],"\u00b1":[213],"0.01":[214],"(p<0.02).":[215],"CONCLUSION:":[216],"The":[217],"demonstrates":[219],"that":[220],"promising":[224],"method":[225,241],"generate":[227],"vectors":[230],"performance.":[234,251],"SIGNIFICANCE:":[235],"This":[236],"presents":[238],"new":[240],"develop":[243]},"counts_by_year":[{"year":2025,"cited_by_count":8},{"year":2024,"cited_by_count":6},{"year":2023,"cited_by_count":7},{"year":2022,"cited_by_count":11},{"year":2021,"cited_by_count":1}],"updated_date":"2026-04-29T09:16:38.111599","created_date":"2025-10-10T00:00:00"}