{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,8,16]],"date-time":"2024-08-16T07:08:29Z","timestamp":1723792109583},"reference-count":56,"publisher":"Elsevier BV","license":[{"start":{"date-parts":[[2023,9,1]],"date-time":"2023-09-01T00:00:00Z","timestamp":1693526400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2023,9,1]],"date-time":"2023-09-01T00:00:00Z","timestamp":1693526400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/legal\/tdmrep-license"},{"start":{"date-parts":[[2023,9,1]],"date-time":"2023-09-01T00:00:00Z","timestamp":1693526400000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-017"},{"start":{"date-parts":[[2023,9,1]],"date-time":"2023-09-01T00:00:00Z","timestamp":1693526400000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"},{"start":{"date-parts":[[2023,9,1]],"date-time":"2023-09-01T00:00:00Z","timestamp":1693526400000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-012"},{"start":{"date-parts":[[2023,9,1]],"date-time":"2023-09-01T00:00:00Z","timestamp":1693526400000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2023,9,1]],"date-time":"2023-09-01T00:00:00Z","timestamp":1693526400000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-004"}],"content-domain":{"domain":["clinicalkey.fr","clinicalkey.jp","clinicalkey.es","clinicalkey.com.au","clinicalkey.com","elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["International Journal of Medical Informatics"],"published-print":{"date-parts":[[2023,9]]},"DOI":"10.1016\/j.ijmedinf.2023.105142","type":"journal-article","created":{"date-parts":[[2023,7,5]],"date-time":"2023-07-05T21:07:24Z","timestamp":1688591244000},"page":"105142","update-policy":"http:\/\/dx.doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":9,"special_numbering":"C","title":["Deep learning-based prediction model for diagnosing gastrointestinal diseases using endoscopy images"],"prefix":"10.1016","volume":"177","author":[{"given":"Anju","family":"Sharma","sequence":"first","affiliation":[]},{"given":"Rajnish","family":"Kumar","sequence":"additional","affiliation":[]},{"given":"Prabha","family":"Garg","sequence":"additional","affiliation":[]}],"member":"78","reference":[{"issue":"5","key":"10.1016\/j.ijmedinf.2023.105142_b0005","doi-asserted-by":"crossref","first-page":"439","DOI":"10.1007\/s12664-018-0892-3","article-title":"Burden of gastrointestinal and liver diseases in India, 1990\u20132016","volume":"37","author":"Shah","year":"2018","journal-title":"Indian J. Gastroenterol."},{"issue":"2","key":"10.1016\/j.ijmedinf.2023.105142_b0010","doi-asserted-by":"crossref","first-page":"338","DOI":"10.1136\/gutjnl-2022-327736","article-title":"Global burden of colorectal cancer in 2020 and 2040: incidence and mortality estimate from GLOBOCAN","volume":"72","author":"Morgan","year":"2023","journal-title":"Gut"},{"issue":"3","key":"10.1016\/j.ijmedinf.2023.105142_b0015","doi-asserted-by":"crossref","first-page":"209","DOI":"10.3322\/caac.21660","article-title":"Global cancer statistics 2020: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries","volume":"71","author":"Sung","year":"2021","journal-title":"CA Cancer J. Clin."},{"issue":"1","key":"10.1016\/j.ijmedinf.2023.105142_b0020","doi-asserted-by":"crossref","first-page":"66","DOI":"10.2174\/0929867328666210405114938","article-title":"Recent applications of artificial intelligence in the detection of gastrointestinal, hepatic and pancreatic diseases","volume":"29","author":"Kumar","year":"2022","journal-title":"Curr. Med. Chem."},{"issue":"3","key":"10.1016\/j.ijmedinf.2023.105142_b0025","doi-asserted-by":"crossref","first-page":"145","DOI":"10.3322\/caac.21601","article-title":"Colorectal cancer statistics, 2020","volume":"70","author":"Siegel","year":"2020","journal-title":"CA Cancer J. Clin."},{"issue":"7","key":"10.1016\/j.ijmedinf.2023.105142_b0030","doi-asserted-by":"crossref","first-page":"511","DOI":"10.1016\/S2468-1253(19)30147-5","article-title":"Changes in colorectal cancer incidence in seven high-income countries: a population-based study","volume":"4","author":"Araghi","year":"2019","journal-title":"Lancet Gastroenterol. Hepatol."},{"key":"10.1016\/j.ijmedinf.2023.105142_b0035","doi-asserted-by":"crossref","unstructured":"P. Mathur, K. Sathishkumar, M. Chaturvedi, P. Das, K.L. Sudarshan, S. Santhappan, V. Nallasamy, A. John, S. Narasimhan, F.S. Roselind, ICMR-NCDIR-NCRP Investigator Group. Cancer Statistics, 2020: Report from National Cancer Registry Programme, India. JCO Glob Oncol. 2020; 6:1063-1075. PMID: 32673076.","DOI":"10.1200\/GO.20.00122"},{"issue":"5","key":"10.1016\/j.ijmedinf.2023.105142_b0040","doi-asserted-by":"crossref","first-page":"1179","DOI":"10.1053\/j.gastro.2012.08.002","article-title":"Burden of gastrointestinal disease in the United States: 2012 update","volume":"143","author":"Peery","year":"2012","journal-title":"Gastroenterology"},{"issue":"6","key":"10.1016\/j.ijmedinf.2023.105142_b0045","doi-asserted-by":"crossref","first-page":"805","DOI":"10.1016\/j.gie.2013.06.026","article-title":"Wireless capsule endoscopy","volume":"78","author":"Technology Committee","year":"2013","journal-title":"Gastrointest. Endosc."},{"key":"10.1016\/j.ijmedinf.2023.105142_b0050","doi-asserted-by":"crossref","unstructured":"R. Sharma, R. Bhadu, S.K. Soni, N. Varma, Reduction of redundant frames in active wireless capsule endoscopy, in: Proceeding of the Second International Conference on Microelectronics, Computing & Communication Systems (MCCS 2017), 2019, pp. 1\u20137.","DOI":"10.1007\/978-981-10-8234-4_1"},{"key":"10.1016\/j.ijmedinf.2023.105142_b0055","doi-asserted-by":"crossref","first-page":"152","DOI":"10.1016\/j.optlastec.2018.08.051","article-title":"Reduction of bubble-like frames using a RSS filter in wireless capsule endoscopy video","volume":"110","author":"Wang","year":"2019","journal-title":"Optics Laser Technol."},{"issue":"25","key":"10.1016\/j.ijmedinf.2023.105142_b0060","doi-asserted-by":"crossref","first-page":"4410","DOI":"10.2174\/0929867329666220222154733","article-title":"Recent applications of artificial intelligence in early cancer detection","volume":"29","author":"Khanam","year":"2022","journal-title":"Curr. Med. Chem."},{"key":"10.1016\/j.ijmedinf.2023.105142_b0065","doi-asserted-by":"crossref","first-page":"251","DOI":"10.1016\/j.irbm.2021.10.003","article-title":"Classification of early stages of esophageal cancer using transfer learning","volume":"43","author":"Ak","year":"2022","journal-title":"IRBM"},{"issue":"1","key":"10.1016\/j.ijmedinf.2023.105142_b0070","doi-asserted-by":"crossref","first-page":"2","DOI":"10.1016\/j.irbm.2020.06.004","article-title":"Cardiovascular disorder severity detection using myocardial anatomic features based optimized extreme learning machine approach","volume":"43","author":"Muthulakshmi","year":"2022","journal-title":"IRBM."},{"issue":"6","key":"10.1016\/j.ijmedinf.2023.105142_b0075","doi-asserted-by":"crossref","first-page":"435","DOI":"10.1016\/j.irbm.2021.06.010","article-title":"Backpropagation neural network for processing of missing data in breast cancer detection","volume":"42","author":"Zhang","year":"2021","journal-title":"IRBM"},{"issue":"2","key":"10.1016\/j.ijmedinf.2023.105142_b0080","doi-asserted-by":"crossref","first-page":"153","DOI":"10.3390\/healthcare9020153","article-title":"A deep learning approach for brain tumor classification and segmentation using a multiscale convolutional neural network","volume":"9","author":"D\u00edaz-Pernas","year":"2021","journal-title":"Healthcare (Basel)."},{"issue":"1","key":"10.1016\/j.ijmedinf.2023.105142_b0085","doi-asserted-by":"crossref","first-page":"6","DOI":"10.1186\/s12880-020-00534-8","article-title":"Melanoma diagnosis using deep learning techniques on dermatoscopic images","volume":"21","author":"Jojoa Acosta","year":"2021","journal-title":"BMC Med. Imag."},{"issue":"12","key":"10.1016\/j.ijmedinf.2023.105142_b0090","doi-asserted-by":"crossref","first-page":"747","DOI":"10.1038\/s41568-021-00399-1","article-title":"Artificial intelligence in cancer research, diagnosis and therapy","volume":"21","author":"Elemento","year":"2021","journal-title":"Nat. Rev. Cancer"},{"issue":"1","key":"10.1016\/j.ijmedinf.2023.105142_b0095","doi-asserted-by":"crossref","first-page":"727","DOI":"10.1038\/s41598-021-04667-w","article-title":"Deep learning-based algorithm for lung cancer detection on chest radiographs using the segmentation method","volume":"12","author":"Shimazaki","year":"2022","journal-title":"Sci. Rep."},{"issue":"2","key":"10.1016\/j.ijmedinf.2023.105142_b0100","doi-asserted-by":"crossref","first-page":"676","DOI":"10.1021\/acs.jcim.0c01288","article-title":"SMILES to smell: decoding the structure-odor relationship of chemical compounds using the deep neural network approach","volume":"61","author":"Sharma","year":"2021","journal-title":"J. Chem. Inf. Model."},{"issue":"34","key":"10.1016\/j.ijmedinf.2023.105142_b0105","doi-asserted-by":"crossref","first-page":"47641","DOI":"10.1007\/s11356-021-14028-9","article-title":"A deep neural network-based approach for prediction of mutagenicity of compounds","volume":"28","author":"Kumar","year":"2021","journal-title":"Environ. Sci. Pollut. Res. Int."},{"issue":"1","key":"10.1016\/j.ijmedinf.2023.105142_b0110","doi-asserted-by":"crossref","first-page":"23","DOI":"10.1016\/j.bbe.2019.11.004","article-title":"Detection of lung cancer on chest CT images using minimum redundancy maximum relevance feature selection method with convolutional neural networks","volume":"40","author":"To\u011fa\u00e7ar","year":"2020","journal-title":"Biocybern. Biomed. Eng."},{"issue":"1","key":"10.1016\/j.ijmedinf.2023.105142_b0115","doi-asserted-by":"crossref","first-page":"169","DOI":"10.1186\/s12916-020-01613-x","article-title":"The challenges of colposcopy for cervical cancer screening in LMICs and solutions by artificial intelligence","volume":"18","author":"Xue","year":"2020","journal-title":"BMC Med."},{"issue":"6","key":"10.1016\/j.ijmedinf.2023.105142_b0120","first-page":"583","article-title":"Application of deep learning to the classification of uterine cervical squamous epithelial lesion from colposcopy images","volume":"11","author":"Miyagi","year":"2019","journal-title":"Mol. Clin. Oncol."},{"issue":"3","key":"10.1016\/j.ijmedinf.2023.105142_b0125","doi-asserted-by":"crossref","first-page":"164","DOI":"10.1016\/j.cmpb.2015.04.002","article-title":"Polyp-Alert: near real-time feedback during colonoscopy","volume":"120","author":"Wang","year":"2015","journal-title":"Comput. Methods Programs Biomed."},{"issue":"10","key":"10.1016\/j.ijmedinf.2023.105142_b0130","doi-asserted-by":"crossref","first-page":"931","DOI":"10.1038\/nmeth.3547","article-title":"Predicting effects of noncoding variants with deep learning-based sequence model","volume":"12","author":"Zhou","year":"2015","journal-title":"Nat. Methods"},{"issue":"8","key":"10.1016\/j.ijmedinf.2023.105142_b0135","doi-asserted-by":"crossref","first-page":"831","DOI":"10.1038\/nbt.3300","article-title":"Predicting the sequence specificities of DNA- and RNA-binding proteins by deep learning","volume":"33","author":"Alipanahi","year":"2015","journal-title":"Nat. Biotechnol."},{"issue":"4","key":"10.1016\/j.ijmedinf.2023.105142_b0140","doi-asserted-by":"crossref","first-page":"244","DOI":"10.2174\/1570163814666170404160911","article-title":"Prediction of human intestinal absorption of compounds using artificial intelligence techniques","volume":"14","author":"Kumar","year":"2017","journal-title":"Curr. Drug Discov. Technol."},{"issue":"3","key":"10.1016\/j.ijmedinf.2023.105142_b0145","doi-asserted-by":"crossref","first-page":"232","DOI":"10.1007\/s12539-011-0102-9","article-title":"A comparative study of support vector machine, artificial neural network and bayesian classifier for mutagenicity prediction","volume":"3","author":"Sharma","year":"2011","journal-title":"Interdiscip. Sci."},{"issue":"17","key":"10.1016\/j.ijmedinf.2023.105142_b0150","doi-asserted-by":"crossref","first-page":"e156","DOI":"10.1093\/nar\/gkx681","article-title":"Using neural networks for reducing the dimensions of single-cell RNA-Seq data","volume":"45","author":"Lin","year":"2017","journal-title":"Nucl. Acids Res."},{"key":"10.1016\/j.ijmedinf.2023.105142_b0155","doi-asserted-by":"crossref","first-page":"17633","DOI":"10.1007\/s00521-021-06347-2","article-title":"OBPred: feature-fusion-based deep neural network classifier for odorant-binding protein prediction","volume":"33","author":"Sharma","year":"2021","journal-title":"Neural Comput. Appl."},{"issue":"16","key":"10.1016\/j.ijmedinf.2023.105142_b0160","doi-asserted-by":"crossref","DOI":"10.1088\/1361-6560\/aad51c","article-title":"Computer-aided detection of small intestinal ulcer and erosion in wireless capsule endoscopy images","volume":"63","author":"Fan","year":"2018","journal-title":"Phys. Med. Biol."},{"key":"10.1016\/j.ijmedinf.2023.105142_b0165","first-page":"1","article-title":"An integrated framework of skin lesion detection and recognition through saliency method and optimal deep neural network features selection","author":"Khan","year":"2019","journal-title":"Neural Comput. Appl."},{"issue":"3","key":"10.1016\/j.ijmedinf.2023.105142_b0170","doi-asserted-by":"crossref","first-page":"172","DOI":"10.1038\/nrgastro.2015.13","article-title":"Software for enhanced video capsule endoscopy: challenges for essential progress","volume":"12","author":"Iakovidis","year":"2015","journal-title":"Nat. Rev. Gastroenterol. Hepatol."},{"key":"10.1016\/j.ijmedinf.2023.105142_b0175","doi-asserted-by":"crossref","DOI":"10.1016\/j.canlet.2023.216238","article-title":"Artificial intelligence in intestinal polyp and colorectal cancer prediction","volume":"565","author":"Sharma","year":"2023","journal-title":"Cancer Lett."},{"key":"10.1016\/j.ijmedinf.2023.105142_b0180","doi-asserted-by":"crossref","first-page":"30","DOI":"10.4103\/jpi.jpi_34_17","article-title":"Deep learning for classification of colorectal polyps on whole-slide images","volume":"8","author":"Korbar","year":"2017","journal-title":"J. Pathol. Inform."},{"issue":"6","key":"10.1016\/j.ijmedinf.2023.105142_b0185","first-page":"6101","article-title":"Deep learning techniques for detecting preneoplastic and neoplastic lesions in human colorectal histological images","volume":"18","author":"Sena","year":"2019","journal-title":"Oncol. Lett."},{"issue":"Suppl 1","key":"10.1016\/j.ijmedinf.2023.105142_b0190","doi-asserted-by":"crossref","first-page":"30","DOI":"10.1159\/000481227","article-title":"Computer-aided diagnosis based on convolutional neural network system for colorectal polyp classification: preliminary experience","volume":"93","author":"Komeda","year":"2017","journal-title":"Oncology"},{"key":"10.1016\/j.ijmedinf.2023.105142_b0195","doi-asserted-by":"crossref","first-page":"149","DOI":"10.1109\/TASE.2016.2610579","article-title":"WCE abnormality detection based on saliency and adaptive locality-constrained linear coding","volume":"14","author":"Yuan","year":"2017","journal-title":"IEEE Trans. Autom. Sci. Eng."},{"key":"10.1016\/j.ijmedinf.2023.105142_b0200","doi-asserted-by":"crossref","first-page":"13091","DOI":"10.1007\/s11042-018-6086-2","article-title":"Multi-scale completed local binary patterns for ulcer detection in wireless capsule endoscopy images","volume":"78","author":"Souaidi","year":"2019","journal-title":"Multimed. Tools Appl."},{"issue":"4","key":"10.1016\/j.ijmedinf.2023.105142_b0205","doi-asserted-by":"crossref","first-page":"1379","DOI":"10.1002\/mp.12147","article-title":"Deep learning for polyp recognition in wireless capsule endoscopy images","volume":"44","author":"Yuan","year":"2017","journal-title":"Med. Phys."},{"key":"10.1016\/j.ijmedinf.2023.105142_b0210","doi-asserted-by":"crossref","first-page":"1097","DOI":"10.3390\/app7101097","article-title":"Feature selection and classification of ulcerated lesions using statistical analysis for WCE images","volume":"7(10)","author":"Suman","year":"2017","journal-title":"Appl. Sci."},{"key":"10.1016\/j.ijmedinf.2023.105142_b0215","doi-asserted-by":"crossref","unstructured":"S. Suman, A.S. Malik, M. Riegler, S.H. Ho, I. Hilmi, K.L. Goh, Detection and classification of bleeding region in WCE images using color feature, in: Proc 15th Int Workshop on Content-Based Multimedia Indexing, 2017, p. 17.","DOI":"10.1145\/3095713.3095731"},{"key":"10.1016\/j.ijmedinf.2023.105142_b0220","doi-asserted-by":"crossref","unstructured":"F. Deeba, S.K. Mohammed, F.M. Bui, K.A. Wahid, Unsupervised abnormality detection using saliency and retinex based color enhancement, in: Proceedings of the 2016 IEEE 38th Annual International Conference of the Engineering in Medicine and Biology Society (EMBC), Orlando, FL, USA, 16\u201320 August 2016, pp. 3871\u20133874.","DOI":"10.1109\/EMBC.2016.7591573"},{"issue":"4","key":"10.1016\/j.ijmedinf.2023.105142_b0225","doi-asserted-by":"crossref","first-page":"1850038","DOI":"10.1142\/S0219519418500380","article-title":"Automated ulcer and bleeding classification from WCE images using multiple features fusion and selection","volume":"18","author":"Liaqat","year":"2018","journal-title":"J. Mech. Med. Biol."},{"key":"10.1016\/j.ijmedinf.2023.105142_b0230","doi-asserted-by":"crossref","first-page":"1265","DOI":"10.3390\/s19061265","article-title":"Application of convolutional neural networks for automated ulcer detection in wireless capsule endoscopy images","volume":"19","author":"Alaskar","year":"2019","journal-title":"Sensors"},{"issue":"1","key":"10.1016\/j.ijmedinf.2023.105142_b0235","doi-asserted-by":"crossref","DOI":"10.1117\/1.JBO.26.1.015001","article-title":"Separation of color channels from conventional colonoscopy images improves deep neural network detection of polyps","volume":"26","author":"Lai","year":"2021","journal-title":"J. Biomed. Opt."},{"issue":"4","key":"10.1016\/j.ijmedinf.2023.105142_b0240","doi-asserted-by":"crossref","first-page":"577","DOI":"10.1080\/0952813X.2019.1572657","article-title":"Deep CNN and geometric features-based gastrointestinal tract diseases detection and classification from wireless capsule endoscopy images","volume":"33","author":"Sharif","year":"2021","journal-title":"J. Exp. Theor. Artif. Intell."},{"key":"10.1016\/j.ijmedinf.2023.105142_b0245","unstructured":"K. Pogorelov, K.R. Randel, C. Griwodz, S.L. Eskeland, T. de Lange, D. Johansen, C. Spampinato, D.T. Dang-Nguyen, M. Lux, P.T. Schmidt, M. Riegler, P. Halvorsen, KVASIR: a multi-class image dataset for computer aided gastrointestinal disease detection. In: Proceedings of the 8th ACM on Multimedia Systems Conference (MMSys'17). association for computing machinery, New York, NY, USA, 2017, pp. 164\u2013169."},{"issue":"1","key":"10.1016\/j.ijmedinf.2023.105142_b0250","doi-asserted-by":"crossref","first-page":"7","DOI":"10.3322\/caac.21551","article-title":"Cancer statistics, 2019","volume":"69","author":"Siegel","year":"2019","journal-title":"CA Cancer J. Clin."},{"issue":"6","key":"10.1016\/j.ijmedinf.2023.105142_b0255","doi-asserted-by":"crossref","first-page":"394","DOI":"10.3322\/caac.21492","article-title":"Global cancer statistics 2018: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries","volume":"68","author":"Bray","year":"2018","journal-title":"CA Cancer J. Clin."},{"key":"10.1016\/j.ijmedinf.2023.105142_b0260","doi-asserted-by":"crossref","first-page":"451","DOI":"10.1007\/978-3-030-37734-2_37","article-title":"Kvasir-SEG: a segmented polyp dataset","author":"Jha","year":"2020","journal-title":"MultiMedia Model."},{"issue":"16","key":"10.1016\/j.ijmedinf.2023.105142_b0265","article-title":"DeePred-BBB: a blood brain barrier permeability prediction model with improved accuracy","volume":"3","author":"Kumar","year":"2022","journal-title":"Front. Neurosci."},{"issue":"1","key":"10.1016\/j.ijmedinf.2023.105142_b0270","doi-asserted-by":"crossref","first-page":"418","DOI":"10.1109\/TCBB.2020.3002154","article-title":"DeepOlf: deep neural network based architecture for predicting odorants and their interacting olfactory receptors","volume":"19","author":"Sharma","year":"2022","journal-title":"IEEE\/ACM Trans. Comput. Biol. Bioinf."},{"issue":"34","key":"10.1016\/j.ijmedinf.2023.105142_b0275","doi-asserted-by":"crossref","first-page":"47641","DOI":"10.1007\/s11356-021-14028-9","article-title":"A deep neural network-based approach for prediction of mutagenicity of compounds","volume":"28","author":"Kumar","year":"2021","journal-title":"Environ. Sci. Pollut. Res. Int."},{"key":"10.1016\/j.ijmedinf.2023.105142_b0280","unstructured":"Chollet, Keras, 2015. (Accessed 21 Nov 2022)."}],"container-title":["International Journal of Medical Informatics"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S1386505623001600?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S1386505623001600?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2024,5,20]],"date-time":"2024-05-20T16:34:12Z","timestamp":1716222852000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S1386505623001600"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,9]]},"references-count":56,"alternative-id":["S1386505623001600"],"URL":"https:\/\/doi.org\/10.1016\/j.ijmedinf.2023.105142","relation":{},"ISSN":["1386-5056"],"issn-type":[{"value":"1386-5056","type":"print"}],"subject":[],"published":{"date-parts":[[2023,9]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"Deep learning-based prediction model for diagnosing gastrointestinal diseases using endoscopy images","name":"articletitle","label":"Article Title"},{"value":"International Journal of Medical Informatics","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.ijmedinf.2023.105142","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2023 Elsevier B.V. All rights reserved.","name":"copyright","label":"Copyright"}],"article-number":"105142"}}