{"id":"https://openalex.org/W7127058230","doi":"https://doi.org/10.28991/esj-2026-010-01-02","title":"Comparative Assessment of Machine Learning Approaches for Early Lung Cancer Diagnosis","display_name":"Comparative Assessment of Machine Learning Approaches for Early Lung Cancer Diagnosis","publication_year":2026,"publication_date":"2026-02-01","ids":{"openalex":"https://openalex.org/W7127058230","doi":"https://doi.org/10.28991/esj-2026-010-01-02"},"language":"en","primary_location":{"id":"doi:10.28991/esj-2026-010-01-02","doi":"https://doi.org/10.28991/esj-2026-010-01-02","is_oa":true,"landing_page_url":"https://doi.org/10.28991/esj-2026-010-01-02","pdf_url":"https://ijournalse.org/index.php/ESJ/article/download/3543/969","source":{"id":"https://openalex.org/S4210232528","display_name":"Emerging Science Journal","issn_l":"2610-9182","issn":["2610-9182"],"is_oa":true,"is_in_doaj":false,"is_core":true,"listed_in":["cwts-core","erih-plus","jufo-1","norway-1","poland-20","russia-white-list-1"],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Emerging Science Journal","raw_type":"journal-article"},"volume":null,"type":"article","is_traditional":true,"indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://ijournalse.org/index.php/ESJ/article/download/3543/969","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5124725971","display_name":"Garvit Maheshwari","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I73779912","display_name":"Manipal University Jaipur","ror":"https://ror.org/040h76494","country_code":"IN","type":"education","lineage":["https://openalex.org/I73779912"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Garvit Maheshwari","raw_affiliation_strings":["Department of Mechanical Engineering, Manipal University Jaipur, Rajasthan, 303007"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Mechanical Engineering, Manipal University Jaipur, Rajasthan, 303007","institution_ids":["https://openalex.org/I73779912"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5121399559","display_name":"Babita Tiwari","orcid":"https://orcid.org/0009-0007-2839-5349","observed_orcids":["https://orcid.org/0009-0007-2839-5349"]},"institutions":[{"id":"https://openalex.org/I73779912","display_name":"Manipal University Jaipur","ror":"https://ror.org/040h76494","country_code":"IN","type":"education","lineage":["https://openalex.org/I73779912"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Babita Tiwari","raw_affiliation_strings":["Department of Computer Science and Engineering, Manipal University Jaipur, Jaipur, Rajasthan"],"raw_orcid":"https://orcid.org/0009-0007-2839-5349","affiliations":[{"raw_affiliation_string":"Department of Computer Science and Engineering, Manipal University Jaipur, Jaipur, Rajasthan","institution_ids":["https://openalex.org/I73779912"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5116001805","display_name":"Domonkos Tinka","orcid":"https://orcid.org/0009-0009-8068-0942","observed_orcids":["https://orcid.org/0009-0009-8068-0942"]},"institutions":[{"id":"https://openalex.org/I83579964","display_name":"Sz\u00e9chenyi Istv\u00e1n University","ror":"https://ror.org/04091f946","country_code":"HU","type":"education","lineage":["https://openalex.org/I83579964"]}],"countries":["HU"],"is_corresponding":false,"raw_author_name":"Domonkos Tinka","raw_affiliation_strings":["Doctoral School of Economic and Regional Sciences, Sz\u00e9chenyi Istv\u00e1n University, 9026 Gy\u0151r"],"raw_orcid":"https://orcid.org/0009-0009-8068-0942","affiliations":[{"raw_affiliation_string":"Doctoral School of Economic and Regional Sciences, Sz\u00e9chenyi Istv\u00e1n University, 9026 Gy\u0151r","institution_ids":["https://openalex.org/I83579964"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5124718269","display_name":"Satyanand Singh","orcid":"https://orcid.org/0000-0002-7707-031X","observed_orcids":["https://orcid.org/0000-0002-7707-031X"]},"institutions":[{"id":"https://openalex.org/I75418795","display_name":"Fiji National University","ror":"https://ror.org/00qk2nf71","country_code":"FJ","type":"education","lineage":["https://openalex.org/I75418795"]}],"countries":["FJ"],"is_corresponding":false,"raw_author_name":"Satyanand Singh","raw_affiliation_strings":["School of Electrical & Electronics Engineering, Fiji National University"],"raw_orcid":"https://orcid.org/0000-0002-7707-031X","affiliations":[{"raw_affiliation_string":"School of Electrical & Electronics Engineering, Fiji National University","institution_ids":["https://openalex.org/I75418795"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":{"value":40,"currency":"USD","value_usd":40},"apc_paid":{"value":40,"currency":"USD","value_usd":40},"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.0,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"10","issue":"1","first_page":"20","last_page":"54"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11396","display_name":"Artificial Intelligence in Healthcare","score":0.9057999849319458,"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"}},"topics":[{"id":"https://openalex.org/T11396","display_name":"Artificial Intelligence in Healthcare","score":0.9057999849319458,"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"}},{"id":"https://openalex.org/T10862","display_name":"AI in cancer detection","score":0.05339999869465828,"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/T10202","display_name":"Lung Cancer Diagnosis and Treatment","score":0.009100000374019146,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/lung-cancer","display_name":"lung cancer","score":0.8560000061988831},{"id":"https://openalex.org/keywords/early-diagnosis","display_name":"early diagnosis","score":0.9750000238418579},{"id":"https://openalex.org/keywords/electronic-health-records","display_name":"electronic health records","score":0.9929999709129333},{"id":"https://openalex.org/keywords/synthetic-patient-data","display_name":"synthetic patient data","score":0.781000018119812},{"id":"https://openalex.org/keywords/metaheuristic-optimization","display_name":"metaheuristic optimization","score":0.675000011920929},{"id":"https://openalex.org/keywords/whale-optimization-algorithm","display_name":"whale optimization algorithm","score":0.8349999785423279},{"id":"https://openalex.org/keywords/xgboost","display_name":"XGBoost","score":0.8130000233650208},{"id":"https://openalex.org/keywords/feature-selection","display_name":"feature selection","score":0.7820000052452087},{"id":"https://openalex.org/keywords/hyperparameter-optimization","display_name":"hyperparameter optimization","score":0.9940000176429749},{"id":"https://openalex.org/keywords/soft-voting-ensemble","display_name":"soft voting ensemble","score":0.7950000166893005},{"id":"https://openalex.org/keywords/ensemble-learning","display_name":"ensemble learning","score":0.8370000123977661},{"id":"https://openalex.org/keywords/computational-efficiency","display_name":"computational efficiency","score":0.6759999990463257}],"concepts":[{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.8463000059127808},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7688999772071838},{"id":"https://openalex.org/C8642999","wikidata":"https://www.wikidata.org/wiki/Q4171168","display_name":"Hyperparameter","level":2,"score":0.7432000041007996},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6504999995231628},{"id":"https://openalex.org/C148483581","wikidata":"https://www.wikidata.org/wiki/Q446488","display_name":"Feature selection","level":2,"score":0.5871000289916992},{"id":"https://openalex.org/C2781162219","wikidata":"https://www.wikidata.org/wiki/Q26250693","display_name":"Replicate","level":2,"score":0.42250001430511475},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.4083999991416931},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.3831000030040741},{"id":"https://openalex.org/C3019952477","wikidata":"https://www.wikidata.org/wiki/Q1324077","display_name":"Health records","level":3,"score":0.37779998779296875},{"id":"https://openalex.org/C169258074","wikidata":"https://www.wikidata.org/wiki/Q245748","display_name":"Random forest","level":2,"score":0.3723999857902527},{"id":"https://openalex.org/C45804977","wikidata":"https://www.wikidata.org/wiki/Q7239673","display_name":"Predictive modelling","level":2,"score":0.35580000281333923},{"id":"https://openalex.org/C66024118","wikidata":"https://www.wikidata.org/wiki/Q1122506","display_name":"Computational model","level":2,"score":0.3330000042915344},{"id":"https://openalex.org/C2776743756","wikidata":"https://www.wikidata.org/wiki/Q5097921","display_name":"Safeguarding","level":2,"score":0.32030001282691956},{"id":"https://openalex.org/C81917197","wikidata":"https://www.wikidata.org/wiki/Q628760","display_name":"Selection (genetic algorithm)","level":2,"score":0.3188999891281128},{"id":"https://openalex.org/C109718341","wikidata":"https://www.wikidata.org/wiki/Q1385229","display_name":"Metaheuristic","level":2,"score":0.31850001215934753},{"id":"https://openalex.org/C10485038","wikidata":"https://www.wikidata.org/wiki/Q48996162","display_name":"Hyperparameter optimization","level":3,"score":0.2768999934196472},{"id":"https://openalex.org/C2776256026","wikidata":"https://www.wikidata.org/wiki/Q47912","display_name":"Lung cancer","level":2,"score":0.27559998631477356},{"id":"https://openalex.org/C147494362","wikidata":"https://www.wikidata.org/wiki/Q2078905","display_name":"Troubleshooting","level":2,"score":0.2718999981880188},{"id":"https://openalex.org/C2778827112","wikidata":"https://www.wikidata.org/wiki/Q22245680","display_name":"Feature engineering","level":3,"score":0.271699994802475},{"id":"https://openalex.org/C2781002164","wikidata":"https://www.wikidata.org/wiki/Q6822311","display_name":"Meta learning (computer science)","level":3,"score":0.2712000012397766},{"id":"https://openalex.org/C93959086","wikidata":"https://www.wikidata.org/wiki/Q6888345","display_name":"Model selection","level":2,"score":0.27090001106262207},{"id":"https://openalex.org/C45942800","wikidata":"https://www.wikidata.org/wiki/Q245652","display_name":"Ensemble learning","level":2,"score":0.26269999146461487},{"id":"https://openalex.org/C117270229","wikidata":"https://www.wikidata.org/wiki/Q5957539","display_name":"Hyper-heuristic","level":5,"score":0.25679999589920044}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.28991/esj-2026-010-01-02","doi":"https://doi.org/10.28991/esj-2026-010-01-02","is_oa":true,"landing_page_url":"https://doi.org/10.28991/esj-2026-010-01-02","pdf_url":"https://ijournalse.org/index.php/ESJ/article/download/3543/969","source":{"id":"https://openalex.org/S4210232528","display_name":"Emerging Science Journal","issn_l":"2610-9182","issn":["2610-9182"],"is_oa":true,"is_in_doaj":false,"is_core":true,"listed_in":["cwts-core","erih-plus","jufo-1","norway-1","poland-20","russia-white-list-1"],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Emerging Science Journal","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.28991/esj-2026-010-01-02","doi":"https://doi.org/10.28991/esj-2026-010-01-02","is_oa":true,"landing_page_url":"https://doi.org/10.28991/esj-2026-010-01-02","pdf_url":"https://ijournalse.org/index.php/ESJ/article/download/3543/969","source":{"id":"https://openalex.org/S4210232528","display_name":"Emerging Science Journal","issn_l":"2610-9182","issn":["2610-9182"],"is_oa":true,"is_in_doaj":false,"is_core":true,"listed_in":["cwts-core","erih-plus","jufo-1","norway-1","poland-20","russia-white-list-1"],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Emerging Science Journal","raw_type":"journal-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/3","display_name":"Good health and well-being","score":0.9391000270843506}],"study_designs":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W7127058230.pdf","grobid_xml":"https://content.openalex.org/works/W7127058230.grobid-xml"},"referenced_works_count":52,"referenced_works":["https://openalex.org/W46659105","https://openalex.org/W883434633","https://openalex.org/W1497256448","https://openalex.org/W1510073064","https://openalex.org/W1678356000","https://openalex.org/W1993760127","https://openalex.org/W2002302337","https://openalex.org/W2053736534","https://openalex.org/W2056132907","https://openalex.org/W2061438946","https://openalex.org/W2076983043","https://openalex.org/W2080966254","https://openalex.org/W2093717447","https://openalex.org/W2122111042","https://openalex.org/W2152195021","https://openalex.org/W2158698691","https://openalex.org/W2165299997","https://openalex.org/W2290883490","https://openalex.org/W2295598076","https://openalex.org/W2333277922","https://openalex.org/W2498119267","https://openalex.org/W2612844530","https://openalex.org/W2760915313","https://openalex.org/W2765982206","https://openalex.org/W2909596766","https://openalex.org/W2911964244","https://openalex.org/W2912934387","https://openalex.org/W2916099831","https://openalex.org/W2943040914","https://openalex.org/W2988507258","https://openalex.org/W3012501605","https://openalex.org/W3015428699","https://openalex.org/W3022907945","https://openalex.org/W3023540311","https://openalex.org/W3087604859","https://openalex.org/W3094294634","https://openalex.org/W3105613063","https://openalex.org/W3128646645","https://openalex.org/W3144747894","https://openalex.org/W3191603129","https://openalex.org/W3215186461","https://openalex.org/W4213009331","https://openalex.org/W4220680732","https://openalex.org/W4239510810","https://openalex.org/W4297957988","https://openalex.org/W4397013501","https://openalex.org/W4398439857","https://openalex.org/W4400378221","https://openalex.org/W4402441511","https://openalex.org/W4404338321","https://openalex.org/W4407664122","https://openalex.org/W4410105881"],"related_works":["https://openalex.org/W4416874700","https://openalex.org/W4417305377","https://openalex.org/W4408579491","https://openalex.org/W4407168847","https://openalex.org/W4409463029","https://openalex.org/W7201831667","https://openalex.org/W4405836993","https://openalex.org/W4409658600","https://openalex.org/W4414876187","https://openalex.org/W7116345110"],"abstract_inverted_index":{"Lung":[0],"cancer,":[1],"a":[2,50,137],"leading":[3],"cause":[4],"of":[5,17,80,115,123,133],"cancer-related":[6],"mortality":[7],"worldwide,":[8],"often":[9],"escapes":[10],"early":[11,33],"detection":[12],"due":[13],"to":[14,54],"the":[15,78,121,155,159],"absence":[16],"distinct":[18],"symptoms":[19],"in":[20,119],"its":[21],"initial":[22],"stages.":[23],"This":[24,140],"work":[25,117],"investigates":[26],"how":[27],"Machine":[28],"Learning":[29],"(ML)":[30],"might":[31],"improve":[32],"diagnosis":[34],"by":[35],"analyzing":[36],"Electronic":[37],"Health":[38],"Records":[39],"(EHR)":[40],"data.":[41],"Multiple":[42],"ML":[43],"models":[44],"were":[45],"developed":[46],"and":[47,74,84,108,125,130],"evaluated":[48],"on":[49],"synthetic":[51,89],"dataset":[52,90,156],"created":[53],"replicate":[55],"real-world":[56],"patient":[57],"characteristics,":[58],"allowing":[59],"controlled":[60],"experimentation":[61],"while":[62,104],"safeguarding":[63],"privacy.":[64],"Model":[65],"performance":[66,149],"was":[67],"tuned":[68],"using":[69],"both":[70],"conventional":[71],"optimization":[72],"methods":[73],"nature-inspired":[75],"approaches,":[76],"with":[77,95,136],"aim":[79],"balancing":[81],"predictive":[82,148],"accuracy":[83,99],"computational":[85,106,151],"efficiency.":[86],"In":[87],"our":[88],"experiments,":[91],"ensemble":[92],"learners":[93],"optimized":[94],"metaheuristic":[96],"techniques":[97],"reached":[98],"levels":[100],"approaching":[101],"99":[102],"percent":[103],"maintaining":[105],"efficiency":[107],"generally":[109],"outperformed":[110],"simpler":[111],"baselines.":[112],"The":[113],"contribution":[114],"this":[116],"lies":[118],"exploring":[120],"integration":[122],"GFO":[124],"WOA":[126],"for":[127,146],"feature":[128],"selection":[129],"hyperparameter":[131],"tuning":[132],"XGBoost,":[134],"together":[135],"soft-voting":[138],"ensemble.":[139],"approach":[141],"provides":[142],"an":[143],"experimental":[144],"pathway":[145],"enhancing":[147],"under":[150],"constraints.":[152],"However,":[153],"as":[154],"is":[157],"synthetic,":[158],"conclusion":[160],"remains":[161],"experimental;":[162],"validation":[163],"against":[164],"clinical":[165],"records":[166],"will":[167],"be":[168],"essential":[169],"before":[170],"translation":[171],"into":[172],"practice.":[173]},"counts_by_year":[],"updated_date":"2026-11-10T11:39:43.021295","created_date":"2026-02-03T00:00:00"}
