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And among all cancers lung and colon cancers are 2 of the most common causes of death and morbidity. The aim of this study was to develop an automated lung and colon cancer classification system using histopathological images. An automated lung and colon classification system was developed using histopathological images from the LC25000 dataset. The algorithm development included data splitting, deep neural network model selection, on the fly image augmentation, training and validation. The core of the algorithm was a Swin Transform V2 model, and 5-fold cross validation was used to evaluate model performance. The model performance was evaluated using Accuracy, Kappa, confusion matrix, precision, recall, and F1. Extensive experiments were conducted to compare the performances of different neural networks including both mainstream convolutional neural networks and vision transformers. The Swin Transform V2 model achieved a 1 (100%) on all metrics, which is the first single model to obtain perfect results on this dataset. The Swin Transformer V2 model has the potential to be used to assist pathologists in classifying lung and colon cancers using histopathology images.<\/jats:p>","DOI":"10.1177\/11795972241271569","type":"journal-article","created":{"date-parts":[[2024,8,15]],"date-time":"2024-08-15T00:00:55Z","timestamp":1723680055000},"update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":21,"title":["Automated Lung and Colon Cancer Classification Using Histopathological Images"],"prefix":"10.1177","volume":"15","author":[{"given":"Jie","family":"Ji","sequence":"first","affiliation":[{"name":"Network & Information Center, Shantou University, Shantou, Guangdong, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jirui","family":"Li","sequence":"additional","affiliation":[{"name":"Guangdong Provincial International Collaborative Center of Molecular Medicine, Laboratory of Molecular Pathology, Shantou University Medical College, Shantou, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9273-7197","authenticated-orcid":false,"given":"Weifeng","family":"Zhang","sequence":"additional","affiliation":[{"name":"Guangdong Provincial International Collaborative Center of Molecular Medicine, Laboratory of Molecular Pathology, Shantou University Medical College, Shantou, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yiqun","family":"Geng","sequence":"additional","affiliation":[{"name":"Guangdong Provincial International Collaborative Center of Molecular Medicine, Laboratory of Molecular Pathology, Shantou University Medical College, Shantou, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yuejiao","family":"Dong","sequence":"additional","affiliation":[{"name":"Department of Pathology, the First Affiliated Hospital of Shantou University Medical College, Shantou, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jiexiong","family":"Huang","sequence":"additional","affiliation":[{"name":"Department of Pathology, the First Affiliated Hospital of Shantou University Medical College, Shantou, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Liangli","family":"Hong","sequence":"additional","affiliation":[{"name":"Department of Pathology, the First Affiliated Hospital of Shantou University Medical College, Shantou, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"179","published-online":{"date-parts":[[2024,8,14]]},"reference":[{"key":"bibr1-11795972241271569","doi-asserted-by":"publisher","DOI":"10.1093\/jnci\/djx030"},{"key":"bibr2-11795972241271569","unstructured":"World Health Organization. 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