{"id":"https://openalex.org/W2903335542","doi":"https://doi.org/10.1109/icacci.2018.8554951","title":"Prediction of Lung Cancer from Low-Resolution Nodules in CT-Scan Images by using Deep Features","display_name":"Prediction of Lung Cancer from Low-Resolution Nodules in CT-Scan Images by using Deep Features","publication_year":2018,"publication_date":"2018-09-01","ids":{"openalex":"https://openalex.org/W2903335542","doi":"https://doi.org/10.1109/icacci.2018.8554951","mag":"2903335542"},"language":"en","primary_location":{"id":"doi:10.1109/icacci.2018.8554951","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icacci.2018.8554951","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 International Conference on Advances in Computing, Communications and Informatics (ICACCI)","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/A5017605774","display_name":"Anand Gupta","orcid":"https://orcid.org/0009-0009-7210-7572"},"institutions":[{"id":"https://openalex.org/I36090812","display_name":"Netaji Subhas University of Technology","ror":"https://ror.org/01fczmh85","country_code":"IN","type":"education","lineage":["https://openalex.org/I36090812"]}],"countries":["IN"],"is_corresponding":true,"raw_author_name":"Anand Gupta","raw_affiliation_strings":["Division of Computer Engineering, Netaji Subhas Institute of Technology, New Delhi, India"],"affiliations":[{"raw_affiliation_string":"Division of Computer Engineering, Netaji Subhas Institute of Technology, New Delhi, India","institution_ids":["https://openalex.org/I36090812"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5007822930","display_name":"Sagorika Das","orcid":null},"institutions":[{"id":"https://openalex.org/I36090812","display_name":"Netaji Subhas University of Technology","ror":"https://ror.org/01fczmh85","country_code":"IN","type":"education","lineage":["https://openalex.org/I36090812"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Sagorika Das","raw_affiliation_strings":["Division of Computer Engineering, Netaji Subhas Institute of Technology, New Delhi, India"],"affiliations":[{"raw_affiliation_string":"Division of Computer Engineering, Netaji Subhas Institute of Technology, New Delhi, India","institution_ids":["https://openalex.org/I36090812"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5077102596","display_name":"Tarasha Khurana","orcid":null},"institutions":[{"id":"https://openalex.org/I36090812","display_name":"Netaji Subhas University of Technology","ror":"https://ror.org/01fczmh85","country_code":"IN","type":"education","lineage":["https://openalex.org/I36090812"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Tarasha Khurana","raw_affiliation_strings":["Division of Computer Engineering, Netaji Subhas Institute of Technology, New Delhi, India"],"affiliations":[{"raw_affiliation_string":"Division of Computer Engineering, Netaji Subhas Institute of Technology, New Delhi, India","institution_ids":["https://openalex.org/I36090812"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5047358399","display_name":"Kamakshi Suri","orcid":null},"institutions":[{"id":"https://openalex.org/I36090812","display_name":"Netaji Subhas University of Technology","ror":"https://ror.org/01fczmh85","country_code":"IN","type":"education","lineage":["https://openalex.org/I36090812"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Kamakshi Suri","raw_affiliation_strings":["Division of Computer Engineering, Netaji Subhas Institute of Technology, New Delhi, India"],"affiliations":[{"raw_affiliation_string":"Division of Computer Engineering, Netaji Subhas Institute of Technology, New Delhi, India","institution_ids":["https://openalex.org/I36090812"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5017605774"],"corresponding_institution_ids":["https://openalex.org/I36090812"],"apc_list":null,"apc_paid":null,"fwci":0.7267,"has_fulltext":false,"cited_by_count":16,"citation_normalized_percentile":{"value":0.74528225,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"531","last_page":"537"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10202","display_name":"Lung Cancer Diagnosis and Treatment","score":0.9998000264167786,"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":0.9998000264167786,"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":0.9979000091552734,"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/T11775","display_name":"COVID-19 diagnosis using AI","score":0.9851999878883362,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.7675724625587463},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7488359808921814},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6997912526130676},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5882254242897034},{"id":"https://openalex.org/keywords/nodule","display_name":"Nodule (geology)","score":0.5597223043441772},{"id":"https://openalex.org/keywords/lung-cancer","display_name":"Lung cancer","score":0.5409612655639648},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.5024142265319824},{"id":"https://openalex.org/keywords/malignancy","display_name":"Malignancy","score":0.4828341603279114},{"id":"https://openalex.org/keywords/computed-tomography","display_name":"Computed tomography","score":0.46819576621055603},{"id":"https://openalex.org/keywords/contextual-image-classification","display_name":"Contextual image classification","score":0.4320535659790039},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.4233490824699402},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.35430455207824707},{"id":"https://openalex.org/keywords/radiology","display_name":"Radiology","score":0.3120163679122925},{"id":"https://openalex.org/keywords/medicine","display_name":"Medicine","score":0.15796509385108948},{"id":"https://openalex.org/keywords/pathology","display_name":"Pathology","score":0.09548327326774597}],"concepts":[{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.7675724625587463},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7488359808921814},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6997912526130676},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5882254242897034},{"id":"https://openalex.org/C2776731575","wikidata":"https://www.wikidata.org/wiki/Q2916245","display_name":"Nodule (geology)","level":2,"score":0.5597223043441772},{"id":"https://openalex.org/C2776256026","wikidata":"https://www.wikidata.org/wiki/Q47912","display_name":"Lung cancer","level":2,"score":0.5409612655639648},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5024142265319824},{"id":"https://openalex.org/C2779399171","wikidata":"https://www.wikidata.org/wiki/Q1483951","display_name":"Malignancy","level":2,"score":0.4828341603279114},{"id":"https://openalex.org/C544519230","wikidata":"https://www.wikidata.org/wiki/Q32566","display_name":"Computed tomography","level":2,"score":0.46819576621055603},{"id":"https://openalex.org/C75294576","wikidata":"https://www.wikidata.org/wiki/Q5165192","display_name":"Contextual image classification","level":3,"score":0.4320535659790039},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.4233490824699402},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.35430455207824707},{"id":"https://openalex.org/C126838900","wikidata":"https://www.wikidata.org/wiki/Q77604","display_name":"Radiology","level":1,"score":0.3120163679122925},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.15796509385108948},{"id":"https://openalex.org/C142724271","wikidata":"https://www.wikidata.org/wiki/Q7208","display_name":"Pathology","level":1,"score":0.09548327326774597},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icacci.2018.8554951","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icacci.2018.8554951","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 International Conference on Advances in Computing, Communications and Informatics (ICACCI)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.800000011920929,"display_name":"Good health and well-being","id":"https://metadata.un.org/sdg/3"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":25,"referenced_works":["https://openalex.org/W54257720","https://openalex.org/W1686810756","https://openalex.org/W1832115302","https://openalex.org/W1898227994","https://openalex.org/W1986649315","https://openalex.org/W1991324991","https://openalex.org/W2013290608","https://openalex.org/W2059483071","https://openalex.org/W2085652537","https://openalex.org/W2144012133","https://openalex.org/W2144513842","https://openalex.org/W2163605009","https://openalex.org/W2294798173","https://openalex.org/W2469075329","https://openalex.org/W2561677464","https://openalex.org/W2584017349","https://openalex.org/W2743008510","https://openalex.org/W2963629121","https://openalex.org/W3008890001","https://openalex.org/W4256741478","https://openalex.org/W4285719527","https://openalex.org/W6602211262","https://openalex.org/W6684191040","https://openalex.org/W6731248135","https://openalex.org/W7075650417"],"related_works":["https://openalex.org/W2092561569","https://openalex.org/W2377100155","https://openalex.org/W2911497689","https://openalex.org/W2952813363","https://openalex.org/W2963346891","https://openalex.org/W4360783045","https://openalex.org/W2770149305","https://openalex.org/W3167930666","https://openalex.org/W3014952856","https://openalex.org/W3010730661"],"abstract_inverted_index":{"Prediction":[0],"of":[1,26,35,59,78,83,92,132,162,176],"lung":[2,73],"cancer":[3,74,88],"from":[4,129,159],"CT-scan":[5,28,107,157],"images":[6,108,158],"is":[7,18,178,193],"viewed":[8],"as":[9,115],"a":[10,27,93,118,151,160,194],"challenging":[11],"task":[12,184],"in":[13,33,67,72,90,100,189,200],"medical":[14],"image":[15,29],"analysis.":[16],"It":[17],"because":[19],"pulmonary":[20],"nodules":[21],"occupy":[22],"less":[23],"than":[24],"5%":[25],"and":[30,40,87,111,143],"vary":[31],"highly":[32],"terms":[34,91],"their":[36],"shape,":[37],"texture,":[38],"opacity":[39],"location,":[41],"making":[42],"it":[43],"difficult":[44],"to":[45,113,117,153],"analyze":[46],"by":[47],"naked":[48],"eye.":[49],"To":[50],"overcome":[51],"this":[52,133,190],"challenge,":[53],"multiple":[54],"approaches":[55,65],"using":[56,185],"digital":[57],"processing":[58],"CT-scans":[60],"are":[61,98,109,137,148,170],"proposed.":[62],"These":[63,96],"existing":[64],"lack":[66,82],"addressing":[68],"three":[69],"main":[70],"challenges":[71,97],"prediction:":[75],"the":[76,101,104,163,167,181,186],"problem":[77],"low":[79],"resolution":[80],"data,":[81],"generalized":[84],"nodule":[85,123,182],"features,":[86],"prediction":[89],"malignancy":[94,155],"score.":[95,156],"addressed":[99],"paper.":[102],"In":[103],"proposed":[105,188],"approach,":[106],"preprocessed":[110],"super-resolved":[112],"serve":[114],"input":[116],"convolutional":[119,134],"neural":[120,135],"network":[121,136],"for":[122,172,180],"region":[124],"detection.":[125],"Deep":[126],"features":[127,147],"engineered":[128],"different":[130],"layers":[131],"classified":[138],"into":[139],"two":[140],"classes:":[141],"benign":[142],"malignant.":[144],"Additionally,":[145],"these":[146],"passed":[149],"through":[150],"regressor":[152],"predict":[154],"subset":[161],"LIDC-IDRI":[164],"dataset,":[165,169],"called":[166],"LUNA16":[168],"used":[171],"experimentation.":[173],"An":[174],"accuracy":[175],"85.7%":[177],"achieved":[179],"classification":[183],"approach":[187],"paper,":[191],"which":[192],"substantial":[195],"improvement":[196],"over":[197],"previous":[198],"works":[199],"literature.":[201]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":4},{"year":2022,"cited_by_count":6},{"year":2020,"cited_by_count":2},{"year":2019,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}