{"id":"https://openalex.org/W2950405065","doi":"https://doi.org/10.1145/3328833.3328872","title":"Feature Extraction and Analysis for Lung Nodule Classification using Random Forest","display_name":"Feature Extraction and Analysis for Lung Nodule Classification using Random Forest","publication_year":2019,"publication_date":"2019-04-09","ids":{"openalex":"https://openalex.org/W2950405065","doi":"https://doi.org/10.1145/3328833.3328872","mag":"2950405065"},"language":"en","primary_location":{"id":"doi:10.1145/3328833.3328872","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3328833.3328872","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2019 8th International Conference on Software and Information Engineering","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/A5012547522","display_name":"Nada S. El-Askary","orcid":"https://orcid.org/0000-0003-0238-5330"},"institutions":[{"id":"https://openalex.org/I107720978","display_name":"Ain Shams University","ror":"https://ror.org/00cb9w016","country_code":"EG","type":"education","lineage":["https://openalex.org/I107720978"]}],"countries":["EG"],"is_corresponding":true,"raw_author_name":"Nada S. El-Askary","raw_affiliation_strings":["Ain Shams University and Information Science, Cairo, Egypt"],"affiliations":[{"raw_affiliation_string":"Ain Shams University and Information Science, Cairo, Egypt","institution_ids":["https://openalex.org/I107720978"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5066592199","display_name":"Mohammed A.\u2010M. Salem","orcid":"https://orcid.org/0000-0003-1489-9830"},"institutions":[{"id":"https://openalex.org/I107720978","display_name":"Ain Shams University","ror":"https://ror.org/00cb9w016","country_code":"EG","type":"education","lineage":["https://openalex.org/I107720978"]},{"id":"https://openalex.org/I96823368","display_name":"German University in Cairo","ror":"https://ror.org/03rjt0z37","country_code":"EG","type":"education","lineage":["https://openalex.org/I96823368"]}],"countries":["EG"],"is_corresponding":false,"raw_author_name":"Mohammed A.-M. Salem","raw_affiliation_strings":["Ain Shams University and Information Science, Cairo, Egypt, German University in Cairo, Cairo, Egypt"],"affiliations":[{"raw_affiliation_string":"Ain Shams University and Information Science, Cairo, Egypt, German University in Cairo, Cairo, Egypt","institution_ids":["https://openalex.org/I96823368","https://openalex.org/I107720978"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5034587442","display_name":"Mohamed Roushdy","orcid":"https://orcid.org/0000-0002-9655-3229"},"institutions":[{"id":"https://openalex.org/I107720978","display_name":"Ain Shams University","ror":"https://ror.org/00cb9w016","country_code":"EG","type":"education","lineage":["https://openalex.org/I107720978"]}],"countries":["EG"],"is_corresponding":false,"raw_author_name":"Mohamed I. Roushdy","raw_affiliation_strings":["Ain Shams University and Information Science, Cairo, Egypt"],"affiliations":[{"raw_affiliation_string":"Ain Shams University and Information Science, Cairo, Egypt","institution_ids":["https://openalex.org/I107720978"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5012547522"],"corresponding_institution_ids":["https://openalex.org/I107720978"],"apc_list":null,"apc_paid":null,"fwci":1.3832,"has_fulltext":false,"cited_by_count":10,"citation_normalized_percentile":{"value":0.82456587,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"248","last_page":"252"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10202","display_name":"Lung Cancer Diagnosis and Treatment","score":0.9965000152587891,"subfield":{"id":"https://openalex.org/subfields/2740","display_name":"Pulmonary and Respiratory Medicine"},"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/T10202","display_name":"Lung Cancer Diagnosis and Treatment","score":0.9965000152587891,"subfield":{"id":"https://openalex.org/subfields/2740","display_name":"Pulmonary and Respiratory Medicine"},"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":0.995199978351593,"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":0.980400025844574,"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":0.7968824505805969},{"id":"https://openalex.org/keywords/random-forest","display_name":"Random forest","score":0.7715316414833069},{"id":"https://openalex.org/keywords/undersampling","display_name":"Undersampling","score":0.7607442140579224},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.714884877204895},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.6580461263656616},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5995389223098755},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.5713174939155579},{"id":"https://openalex.org/keywords/preprocessor","display_name":"Preprocessor","score":0.49271848797798157},{"id":"https://openalex.org/keywords/contextual-image-classification","display_name":"Contextual image classification","score":0.48494580388069153},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.4625090956687927},{"id":"https://openalex.org/keywords/nodule","display_name":"Nodule (geology)","score":0.42930787801742554},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.1993643343448639}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7968824505805969},{"id":"https://openalex.org/C169258074","wikidata":"https://www.wikidata.org/wiki/Q245748","display_name":"Random forest","level":2,"score":0.7715316414833069},{"id":"https://openalex.org/C136536468","wikidata":"https://www.wikidata.org/wiki/Q1225894","display_name":"Undersampling","level":2,"score":0.7607442140579224},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.714884877204895},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.6580461263656616},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5995389223098755},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.5713174939155579},{"id":"https://openalex.org/C34736171","wikidata":"https://www.wikidata.org/wiki/Q918333","display_name":"Preprocessor","level":2,"score":0.49271848797798157},{"id":"https://openalex.org/C75294576","wikidata":"https://www.wikidata.org/wiki/Q5165192","display_name":"Contextual image classification","level":3,"score":0.48494580388069153},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.4625090956687927},{"id":"https://openalex.org/C2776731575","wikidata":"https://www.wikidata.org/wiki/Q2916245","display_name":"Nodule (geology)","level":2,"score":0.42930787801742554},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.1993643343448639},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3328833.3328872","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3328833.3328872","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2019 8th International Conference on Software and Information Engineering","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/15","display_name":"Life in Land","score":0.6399999856948853}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":31,"referenced_works":["https://openalex.org/W67767829","https://openalex.org/W1526532708","https://openalex.org/W1559121794","https://openalex.org/W1651586605","https://openalex.org/W1779959761","https://openalex.org/W1797580880","https://openalex.org/W1930624869","https://openalex.org/W1974165720","https://openalex.org/W1986649315","https://openalex.org/W1992122542","https://openalex.org/W1995567168","https://openalex.org/W2003304826","https://openalex.org/W2015450448","https://openalex.org/W2044465660","https://openalex.org/W2061409412","https://openalex.org/W2066720700","https://openalex.org/W2067123389","https://openalex.org/W2067197327","https://openalex.org/W2083927153","https://openalex.org/W2113242816","https://openalex.org/W2127227873","https://openalex.org/W2330365780","https://openalex.org/W2469075329","https://openalex.org/W2520657381","https://openalex.org/W2580434384","https://openalex.org/W2659698999","https://openalex.org/W2911964244","https://openalex.org/W2912934387","https://openalex.org/W3105902188","https://openalex.org/W3122150008","https://openalex.org/W4296886862"],"related_works":["https://openalex.org/W2109073422","https://openalex.org/W2887783772","https://openalex.org/W2101754595","https://openalex.org/W4249381695","https://openalex.org/W2534887053","https://openalex.org/W2026172757","https://openalex.org/W2080076470","https://openalex.org/W4389292014","https://openalex.org/W3165582150","https://openalex.org/W4293261997"],"abstract_inverted_index":{"Early":[0],"detection":[1,46],"of":[2,8],"lung":[3,12,27,37],"nodule":[4,38],"decreases":[5],"the":[6,26,62,79,95,102,112,129,184],"risk":[7],"advanced":[9],"stages":[10,51],"in":[11],"cancer":[13],"disease.":[14],"Random":[15],"forest":[16],"(RF),":[17],"a":[18],"machine":[19,134],"learning":[20,135],"classifier,":[21],"is":[22,41,67,74,84,100,107,128],"used":[23],"to":[24,43,116,132,147],"detect":[25],"nodules":[28,33],"and":[29,34,56,70,93,141,149,160,174,190,195],"classify":[30],"soft-tissues":[31],"into":[32],"non-nodules.":[35],"A":[36,49],"classification":[39,154],"approach":[40],"proposed":[42,144,185],"improve":[44],"early":[45],"for":[47,121,165,176,192],"nodules.":[48],"five":[50],"model":[52,186],"has":[53],"been":[54],"built":[55],"tested":[57],"using":[58],"165":[59],"cases":[60],"from":[61,78,111],"LIDC":[63],"database.":[64],"Stage":[65,72,82,98,105],"1":[66],"image":[68],"acquisition":[69],"preprocessing.":[71],"2":[73],"extracting":[75],"119":[76],"features":[77,151],"CT":[80],"image.":[81],"3":[83],"refining":[85],"feature":[86,114,158],"vectors":[87],"by":[88,126,183],"removing":[89],"all":[90],"duplicate":[91],"instances":[92],"undersampling":[94],"non-nodule":[96],"class.":[97],"4":[99],"tuning":[101],"RF":[103,127,168],"parameters.":[104],"5":[106],"examining":[108],"different":[109],"collections":[110],"extracted":[113],"sets":[115],"select":[117,150],"those":[118],"scores":[119],"best":[120,164],"classification.":[122],"The":[123,143],"accuracy":[124,196],"achieved":[125,182],"highest":[130],"compared":[131],"other":[133],"classifiers":[136],"such":[137],"as":[138],"KNN,":[139],"SVM,":[140],"DT.":[142],"method":[145],"aimed":[146],"analyze":[148],"that":[152],"maximize":[153],"results.":[155],"Pixel":[156],"based":[157],"set":[159,162],"wavelet-based":[161],"scored":[163],"higher":[166],"accuracy.":[167],"was":[169],"tuned":[170],"with":[171],"170":[172],"trees":[173],"0.007":[175],"in-bag":[177],"fraction.":[178],"Best":[179],"results":[180],"were":[181],"are":[187],"90.67%,":[188],"90.8%":[189],"90.73%":[191],"sensitivity,":[193],"specificity,":[194],"respectively.":[197]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":5},{"year":2021,"cited_by_count":2},{"year":2019,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}