{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,22]],"date-time":"2026-06-22T18:09:30Z","timestamp":1782151770891,"version":"3.54.5"},"reference-count":26,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2024,5,15]],"date-time":"2024-05-15T00:00:00Z","timestamp":1715731200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2024,5,15]],"date-time":"2024-05-15T00:00:00Z","timestamp":1715731200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Health Inf Sci Syst"],"DOI":"10.1007\/s13755-024-00294-7","type":"journal-article","created":{"date-parts":[[2024,5,15]],"date-time":"2024-05-15T10:02:11Z","timestamp":1715767331000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":11,"title":["Harbor seal whiskers optimization algorithm with deep learning-based medical imaging analysis for gastrointestinal cancer detection"],"prefix":"10.1007","volume":"12","author":[{"given":"Amal","family":"Alshardan","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Muhammad Kashif","family":"Saeed","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Shoayee Dlaim","family":"Alotaibi","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Abdullah M.","family":"Alashjaee","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Nahla","family":"Salih","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Radwa","family":"Marzouk","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2024,5,15]]},"reference":[{"key":"294_CR1","volume-title":"Seminars in cancer biology","author":"Z Wang","year":"2023","unstructured":"Wang Z, Liu Y, Niu X. Application of artificial intelligence for improving early detection and prediction of therapeutic outcomes for gastric cancer in the era of precision oncology. In: Seminars in cancer biology. Academic Press; 2023."},{"key":"294_CR2","doi-asserted-by":"crossref","unstructured":"Sharanyaa S, Vijayalakshmi S, Therasa M, Kumaran U, Deepika R. DCNET: a novel implementation of gastric cancer detection system through deep learning convolution networks. In 2022 international conference on advanced computing technologies and applications (ICACTA) (pp. 1\u20135). IEEE; 2022.","DOI":"10.1109\/ICACTA54488.2022.9752960"},{"key":"294_CR3","doi-asserted-by":"crossref","unstructured":"Su X, Liu Q, Gao X, Ma L. Evaluation of deep learning methods for early gastric cancer detection using gastroscopic images. Technology and Health Care, (Preprint), 2023:1\u201310.","DOI":"10.3233\/THC-236027"},{"issue":"3","key":"294_CR4","doi-asserted-by":"publisher","first-page":"1535","DOI":"10.1002\/mp.15437","volume":"49","author":"C Li","year":"2022","unstructured":"Li C, Qin Y, Zhang WH, Jiang H, Song B, Bashir MR, Xu H, Duan T, Fang M, Zhong L, Meng L. Deep learning-based AI model for signet-ring cell carcinoma diagnosis and chemotherapy response prediction in gastric cancer. Med Phys. 2022;49(3):1535\u201346.","journal-title":"Med Phys"},{"key":"294_CR5","doi-asserted-by":"publisher","first-page":"105336","DOI":"10.1016\/j.bspc.2023.105336","volume":"86","author":"Z Guo","year":"2023","unstructured":"Guo Z, Lan J, Wang J, Hu Z, Wu Z, Quan J, Han Z, Wang T, Du M, Gao Q, Xue Y. Prediction of lymph node metastasis in primary gastric cancer from pathological images and clinical data by multimodal multiscale deep learning. Biomed Signal Process Control. 2023;86:105336.","journal-title":"Biomed Signal Process Control"},{"issue":"10","key":"294_CR6","doi-asserted-by":"publisher","first-page":"7800","DOI":"10.1007\/s00464-022-09319-2","volume":"36","author":"D Tang","year":"2022","unstructured":"Tang D, Ni M, Zheng C, Ding X, Zhang N, Yang T, Zhan Q, Fu Y, Liu W, Zhuang D, Lv Y. A deep learning-based model improves the diagnosis of early gastric cancer under narrow-band imaging endoscopy. Surg Endosc. 2022;36(10):7800\u201310.","journal-title":"Surg Endosc"},{"key":"294_CR7","doi-asserted-by":"publisher","DOI":"10.1093\/bfgp\/elad032","author":"J Li","year":"2023","unstructured":"Li J, Liu H, Liu W, Zong P, Huang K, Li Z, Li H, Xiong T, Tian G, Li C, Yang J. Predicting gastric cancer tumour mutational burden from histopathological images using multimodal deep learning. Brief Funct Genomics. 2023. https:\/\/doi.org\/10.1093\/bfgp\/elad032.","journal-title":"Brief Funct Genomics"},{"issue":"4","key":"294_CR8","doi-asserted-by":"publisher","first-page":"599","DOI":"10.1016\/j.gie.2021.12.021","volume":"95","author":"F Xie","year":"2022","unstructured":"Xie F, Zhang K, Li F, Ma G, Ni Y, Zhang W, Wang J, Li Y. Diagnostic accuracy of convolutional neural network\u2013based endoscopic image analysis in diagnosing gastric cancer and predicting its invasion depth: a systematic review and meta-analysis. Gastrointest Endosc. 2022;95(4):599\u2013609.","journal-title":"Gastrointest Endosc"},{"issue":"2","key":"294_CR9","first-page":"100561","volume":"16","author":"Z Zhang","year":"2023","unstructured":"Zhang Z, Peng J. Clinical nursing and postoperative prediction of gastrointestinal cancer based on CT deep learning model. J Radiat Res Appl Sci. 2023;16(2):100561.","journal-title":"J Radiat Res Appl Sci"},{"issue":"9","key":"294_CR10","doi-asserted-by":"publisher","first-page":"1262","DOI":"10.1038\/s41379-022-01073-z","volume":"35","author":"W Ba","year":"2022","unstructured":"Ba W, Wang S, Shang M, Zhang Z, Wu H, Yu C, Xing R, Wang W, Wang L, Liu C, Shi H. Assessment of deep learning assistance for the pathological diagnosis of gastric cancer. Mod Pathol. 2022;35(9):1262\u20138.","journal-title":"Mod Pathol"},{"key":"294_CR11","doi-asserted-by":"publisher","first-page":"104261","DOI":"10.1016\/j.bspc.2022.104261","volume":"79","author":"Z Hu","year":"2023","unstructured":"Hu Z, Deng Y, Lan J, Wang T, Han Z, Huang Y, Zhang H, Wang J, Cheng M, Jiang H, Lee RG. A multi-task deep learning framework for perineural invasion recognition in gastric cancer whole slide images. Biomed Signal Process Control. 2023;79:104261.","journal-title":"Biomed Signal Process Control"},{"key":"294_CR12","doi-asserted-by":"publisher","first-page":"106210","DOI":"10.1016\/j.cmpb.2021.106210","volume":"207","author":"J Wang","year":"2021","unstructured":"Wang J, Liu X. Medical image recognition and segmentation of pathological slices of gastric cancer based on Deeplab v3+ neural network. Comput Methods Programs Biomed. 2021;207:106210.","journal-title":"Comput Methods Programs Biomed"},{"key":"294_CR13","doi-asserted-by":"publisher","first-page":"105207","DOI":"10.1016\/j.compbiomed.2021.105207","volume":"142","author":"W Hu","year":"2022","unstructured":"Hu W, Li C, Li X, Rahaman MM, Ma J, Zhang Y, Chen H, Liu W, Sun C, Yao Y, Sun H. GasHisSDB: A new gastric histopathology image dataset for computer-aided diagnosis of gastric cancer. Comput Biol Med. 2022;142:105207.","journal-title":"Comput Biol Med"},{"key":"294_CR14","doi-asserted-by":"publisher","first-page":"104200","DOI":"10.1016\/j.bspc.2022.104200","volume":"79","author":"L Ma","year":"2023","unstructured":"Ma L, Su X, Ma L, Gao X, Sun M. Deep learning for classification and localization of early gastric cancer in endoscopic images. Biomed Signal Process Control. 2023;79:104200.","journal-title":"Biomed Signal Process Control"},{"issue":"05","key":"294_CR15","doi-asserted-by":"publisher","first-page":"469","DOI":"10.1055\/a-1229-0920","volume":"53","author":"T Ling","year":"2021","unstructured":"Ling T, Wu L, Fu Y, Xu Q, An P, Zhang J, Hu S, Chen Y, He X, Wang J, Chen X. A deep learning-based system for identifying differentiation status and delineating the margins of early gastric cancer in magnifying narrow-band imaging endoscopy. Endoscopy. 2021;53(05):469\u201377.","journal-title":"Endoscopy"},{"issue":"3","key":"294_CR16","doi-asserted-by":"publisher","first-page":"e12758","DOI":"10.1111\/exsy.12758","volume":"39","author":"W Qiu","year":"2022","unstructured":"Qiu W, Xie J, Shen Y, Xu J, Liang J. Endoscopic image recognition method of gastric cancer based on deep learning model. Expert Syst. 2022;39(3):e12758.","journal-title":"Expert Syst"},{"key":"294_CR17","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2023.3297441","author":"OM Mirza","year":"2023","unstructured":"Mirza OM, Alsobhi A, Hasanin T, Ishak MK, Karim FK, Mostafa SM. Computer aided diagnosis for gastrointestinal cancer classification using hybrid rice optimization with deep learning. IEEE Access. 2023. https:\/\/doi.org\/10.1109\/ACCESS.2023.3297441.","journal-title":"IEEE Access"},{"issue":"1","key":"294_CR18","doi-asserted-by":"publisher","first-page":"2790","DOI":"10.1038\/s41467-022-30459-5","volume":"13","author":"X Zheng","year":"2022","unstructured":"Zheng X, Wang R, Zhang X, Sun Y, Zhang H, Zhao Z, Zheng Y, Luo J, Zhang J, Wu H, Huang D. A deep learning model and human-machine fusion for prediction of EBV-associated gastric cancer from histopathology. Nat Commun. 2022;13(1):2790.","journal-title":"Nat Commun"},{"issue":"5","key":"294_CR19","first-page":"180","volume":"3","author":"S Das","year":"2015","unstructured":"Das S, Saikia J, Das S, Goni NA. Comparative study of different noise filtering techniques in digital images. Int J Eng Res Gen Sci. 2015;3(5):180\u201391.","journal-title":"Int J Eng Res Gen Sci"},{"key":"294_CR20","doi-asserted-by":"publisher","first-page":"6415","DOI":"10.3934\/mbe.2022301","volume":"19","author":"S Shinde","year":"2022","unstructured":"Shinde S, Kalbhor M, Wajire P. DeepCyto: a hybrid framework for cervical cancer classification by using deep feature fusion of cytology images. Math Biosci Eng. 2022;19:6415\u201334.","journal-title":"Math Biosci Eng"},{"key":"294_CR21","doi-asserted-by":"publisher","first-page":"88","DOI":"10.1016\/j.aej.2023.08.040","volume":"80","author":"H Zaher","year":"2023","unstructured":"Zaher H, Al-Wahsh H, Eid MH, Gad RS, Abdel-Rahim N, Abdelqawee IM. A novel harbor seal whiskers optimization algorithm. Alex Eng J. 2023;80:88\u2013109.","journal-title":"Alex Eng J"},{"issue":"16","key":"294_CR22","doi-asserted-by":"publisher","first-page":"3506","DOI":"10.3390\/electronics12163506","volume":"12","author":"T Li","year":"2023","unstructured":"Li T, Li T, Su R, Xin J, Han D. Classification and recognition of goat movement behavior based on SL-WOA-XGBoost. Electronics. 2023;12(16):3506.","journal-title":"Electronics"},{"key":"294_CR23","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2023.3281508","author":"P Venkatasaichandrakanth","year":"2023","unstructured":"Venkatasaichandrakanth P, Iyapparaja M. Pest detection and classification in peanut crops using CNN, MFO, and EViTA algorithms. IEEE Access. 2023. https:\/\/doi.org\/10.1109\/ACCESS.2023.3281508.","journal-title":"IEEE Access"},{"key":"294_CR24","unstructured":"https:\/\/datasets.simula.no\/kvasir-seg\/"},{"key":"294_CR25","doi-asserted-by":"crossref","unstructured":"Godkhindi AM, Gowda RM. Automated detection of polyps in CT colonography images using deep learning algorithms in colon cancer diagnosis. In: Proceedings of the 2017 International Conference on Energy, Communication, Data Analytics and Soft Computing (ICECDS), pp. 1722\u20131728, IEEE, August 2017.","DOI":"10.1109\/ICECDS.2017.8389744"},{"key":"294_CR26","doi-asserted-by":"crossref","unstructured":"Fonoll\u00b4a R, Van Der Sommen F, Schreuder RM, Schoon EJ, De With PH. Multi-modal classification of polyp malignancy using CNN features with balanced class augmentation. In Proceedings of the 2019 IEEE 16th International Symposium on Biomedical Imaging (ISBI 2019), pp. 74\u201378, IEEE, Venice, Italy, April 2019.","DOI":"10.1109\/ISBI.2019.8759320"}],"container-title":["Health Information Science and Systems"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s13755-024-00294-7.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s13755-024-00294-7\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s13755-024-00294-7.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,12,3]],"date-time":"2024-12-03T08:29:14Z","timestamp":1733214554000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s13755-024-00294-7"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,5,15]]},"references-count":26,"journal-issue":{"issue":"1","published-online":{"date-parts":[[2024,12]]}},"alternative-id":["294"],"URL":"https:\/\/doi.org\/10.1007\/s13755-024-00294-7","relation":{},"ISSN":["2047-2501"],"issn-type":[{"value":"2047-2501","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024,5,15]]},"assertion":[{"value":"28 March 2024","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"29 April 2024","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"15 May 2024","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"The authors declare that they have no conflict of interest. The manuscript was written through contributions of all authors. All authors have given approval to the final version of the manuscript.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interest"}},{"value":"This article does not contain any studies with human participants performed by any of the authors.","order":3,"name":"Ethics","group":{"name":"EthicsHeading","label":"Ethical approval"}},{"value":"Not applicable.","order":4,"name":"Ethics","group":{"name":"EthicsHeading","label":"Consent to participate"}},{"value":"Not applicable.","order":5,"name":"Ethics","group":{"name":"EthicsHeading","label":"Informed consent"}}],"article-number":"35"}}