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Lung cancer is notoriously difficult to diagnose until it has progressed to a late stage, making it a leading cause of cancer-related mortality. Lung cancer is fatal if not treated early, making this a significant issue. Initial diagnosis of malignant nodules is often made using chest radiography (X-ray) and computed tomography (CT) scans; nevertheless, the possibility of benign nodules leads to wrong choices. In their first phases, benign and malignant nodules seem very similar. Additionally, radiologists have a hard time viewing and categorizing lung abnormalities. Lung cancer screenings performed by radiologists are often performed with the use of computer-aided diagnostic technologies. Computer scientists have presented many methods for identifying lung cancer in recent years. Low-quality images compromise the segmentation process, rendering traditional lung cancer prediction algorithms inaccurate. This article suggests a highly effective strategy for identifying and categorizing lung cancer. Noise in the pictures was reduced using a weighted filter, and the improved Gray Wolf Optimization method was performed before segmentation with watershed modification and dilation operations. We used InceptionNet-V3 to classify lung cancer into three groups, and it performed well compared to prior studies: 98.96% accuracy, 94.74% specificity, as well as 100% sensitivity.<\/jats:p>","DOI":"10.3390\/s22249603","type":"journal-article","created":{"date-parts":[[2022,12,8]],"date-time":"2022-12-08T03:35:53Z","timestamp":1670470553000},"page":"9603","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":64,"title":["IGWO-IVNet3: DL-Based Automatic Diagnosis of Lung Nodules Using an Improved Gray Wolf Optimization and InceptionNet-V3"],"prefix":"10.3390","volume":"22","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-7760-3374","authenticated-orcid":false,"given":"Anas","family":"Bilal","sequence":"first","affiliation":[{"name":"College of Information Science and Technology, Hainan Normal University, Haikou 571158, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3724-6528","authenticated-orcid":false,"given":"Muhammad","family":"Shafiq","sequence":"additional","affiliation":[{"name":"School of Information Engineering, Qujing Normal University, Qujing 655011, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Fang","family":"Fang","sequence":"additional","affiliation":[{"name":"College of Information Engineering, Hainan Vocational University of Science and Technology, Haikou 571126, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Muhammad","family":"Waqar","sequence":"additional","affiliation":[{"name":"Department of Computer Science, COMSATS University, Islamabad 45550, Pakistan"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5879-569X","authenticated-orcid":false,"given":"Inam","family":"Ullah","sequence":"additional","affiliation":[{"name":"BK21 Chungbuk Information Technology Education and Research Center, Chungbuk National University, Cheongju-si 28644, Republic of Korea"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7121-495X","authenticated-orcid":false,"given":"Yazeed Yasin","family":"Ghadi","sequence":"additional","affiliation":[{"name":"Department of Computer Science, Al Ain University, Abu Dhabi 64141, United Arab Emirates"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2202-3820","authenticated-orcid":false,"given":"Haixia","family":"Long","sequence":"additional","affiliation":[{"name":"College of Information Science and Technology, Hainan Normal University, Haikou 571158, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2025-9904","authenticated-orcid":false,"given":"Rao","family":"Zeng","sequence":"additional","affiliation":[{"name":"College of Information Science and Technology, Hainan Normal University, Haikou 571158, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2022,12,7]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"34","DOI":"10.4161\/epi.6.1.13313","article-title":"Comparison of Methyl-DNA Immunoprecipitation (MeDIP) and Methyl-CpG Binding Domain (MBD) Protein Capture for Genome-Wide DNA Methylation Analysis Reveal CpG Sequence Coverage Bias","volume":"6","author":"Nair","year":"2011","journal-title":"Epigenetics"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"315","DOI":"10.1007\/s13273-018-0034-0","article-title":"Identification of Lung Cancer Specific Differentially Methylated Regions Using Genome-Wide DNA Methylation Study","volume":"14","author":"Hong","year":"2018","journal-title":"Mol. 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