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For: Niu PH, Zhao LL, Wu HL, Zhao DB, Chen YT. Artificial intelligence in gastric cancer: Application and future perspectives. World J Gastroenterol 2020; 26(36): 5408-5419 [PMID: 33024393 DOI: 10.3748/wjg.v26.i36.5408]
URL: https://www.wjgnet.com/2644-3236/full/v26/i36/5408.htm
Number Citing Articles
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Khalid Nawab, Ravi Athwani, Awais Naeem, Muhammad Hamayun, Momna Wazir. A Review of Applications of Artificial Intelligence in GastroenterologyCureus 2021;  doi: 10.7759/cureus.19235
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Qing Li, Bing-Rong Liu. Application of artificial intelligence-assisted endoscopic detection of early esophageal cancerWorld Chinese Journal of Digestology 2021; 29(24): 1389 doi: 10.11569/wcjd.v29.i24.1389
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4
Maria Antonietta Mazzei, Nunzia Di Meglio, Francesco Gentili, Giulio Bagnacci, Raffaele Macchiarelli, Luca Volterrani. Multimodality Imaging and Intervention in Oncology2023; : 227 doi: 10.1007/978-3-031-28524-0_11
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Shahid Aziz, Simone König, Muhammad Umer, Tayyab Saeed Akhter, Shafqat Iqbal, Maryum Ibrar, Tofeeq Ur-Rehman, Tanvir Ahmad, Alfizah Hanafiah, Rabaab Zahra, Faisal Rasheed. Risk factor profiles for gastric cancer prediction with respect to <i>Helicobacter pylori</i>: A study of a tertiary care hospital in PakistanArtificial Intelligence in Gastroenterology 2023; 4(1): 10-27 doi: 10.35712/aig.v4.i1.10
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Olfat M. Mirza, Aisha Alsobhi, Tawfiq Hasanin, Mohamad Khairi Ishak, Faten Khalid Karim, Samih M. Mostafa. Computer Aided Diagnosis for Gastrointestinal Cancer Classification Using Hybrid Rice Optimization With Deep LearningIEEE Access 2023; 11: 76321 doi: 10.1109/ACCESS.2023.3297441
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Antonello FORGIONE, Salman Y. GURAYA, Michele DIANA, Jacques MARESCAUX. Intraoperative and postoperative complications in colorectal procedures: the role of continuous updating in medicineMinerva Surgery 2021; 76(4) doi: 10.23736/S2724-5691.21.08638-X
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Yuzhang Xie, Guoshuai Niu, Qian Da, Wentao Dai, Yang Yang. Survival Prediction for Gastric Cancer via Multimodal Learning of Whole Slide Images and Gene Expression2022 IEEE International Conference on Bioinformatics and Biomedicine (BIBM) 2022; : 1311 doi: 10.1109/BIBM55620.2022.9995480
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Tsutomu Hayashi, Ken Takasawa, Takaki Yoshikawa, Taiki Hashimoto, Shigeki Sekine, Takeyuki Wada, Yukinori Yamagata, Haruhisa Suzuki, Seiichirou Abe, Shigetaka Yoshinaga, Yutaka Saito, Nobuji Kouno, Ryuji Hamamoto. A discrimination model by machine learning to avoid gastrectomy for early gastric cancerAnnals of Gastroenterological Surgery 2023; 7(6): 913 doi: 10.1002/ags3.12714
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Nfn Kiran, FNU Sapna, FNU Kiran, Deepak Kumar, FNU Raja, Sheena Shiwlani, Antonella Paladini, FNU Sonam, Ahmed Bendari, Raja Sandeep Perkash, FNU Anjali, Giustino Varrassi. Digital Pathology: Transforming Diagnosis in the Digital AgeCureus 2023;  doi: 10.7759/cureus.44620
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Alexandra Orășeanu, Mihaela Cristina Brisc, Octavian Adrian Maghiar, Horia Popa, Ciprian Mihai Brisc, Sabina Florina Șolea, Teodor Andrei Maghiar, Ciprian Brisc. Landscape of Innovative Methods for Early Diagnosis of Gastric Cancer: A Systematic ReviewDiagnostics 2023; 13(24): 3608 doi: 10.3390/diagnostics13243608
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Yousun Ko, Hooyoung Shin, Juneseuk Shin, Hoon Hur, Jimi Huh, Taeyong Park, Kyung Won Kim, In-Seob Lee. Artificial Intelligence Mortality Prediction Model for Gastric Cancer Surgery Based on Body Morphometry, Nutritional, and Surgical Information: Feasibility StudyApplied Sciences 2022; 12(8): 3873 doi: 10.3390/app12083873
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Hao Zhang, Jiayi Qian, Ming Jin, Li Fan, SongJie Fan, Hong Pan, Yang Li, Ningning Wang, Baiyu Jian. Jolkinolide B induces cell cycle arrest and apoptosis in MKN45 gastric cancer cells and inhibits xenograft tumor growth in vivo Bioscience Reports 2022; 42(6) doi: 10.1042/BSR20220341
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Hiroshi Yoshida, Tomoharu Kiyuna. Requirements for implementation of artificial intelligence in the practice of gastrointestinal pathologyWorld Journal of Gastroenterology 2021; 27(21): 2818-2833 doi: 10.3748/wjg.v27.i21.2818
15
Atefeh Talebi, Nasrin Borumandnia, Hassan Doosti, Somayeh Abbasi, Mohamad Amin Pourhoseingholi, Shahram Agah, Seidamir Pasha Tabaeian. Development of web-based dynamic nomogram to predict survival in patients with gastric cancer: a population-based studyScientific Reports 2022; 12(1) doi: 10.1038/s41598-022-08465-w
16
Bowen Zhang, Long Cheng, Yuzhen Niu, Aming Wang, Pengyi Zhang, Tiantian Shen, Lili Xi, Dekui Zhang, Shuyan Li. Identification Tool for Gastric Cancer Based on Integration of 33 Clinical Available Blood Indices Through Deep LearningIEEE Access 2022; 10: 106081 doi: 10.1109/ACCESS.2022.3172477
17
Julian Andres Ramirez-Bautista, Silvia L. Chaparro-Cárdenas, Carmen Esmer, Jorge Adalberto Huerta-Ruelas. Artificial intelligence approaches to physiological parameter analysis in the monitoring and treatment of non-communicable diseases: A reviewBiomedical Signal Processing and Control 2024; 87: 105463 doi: 10.1016/j.bspc.2023.105463
18
Roberto Castro, Leo Ramos, Stadyn Román, Mike Bermeo, Anthony Crespo, Erick Cuenca. Applied TechnologiesCommunications in Computer and Information Science 2023; 1755: 212 doi: 10.1007/978-3-031-24985-3_16
19
Atefeh Talebi, Carlos A. Celis-Morales, Nasrin Borumandnia, Somayeh Abbasi, Mohamad Amin Pourhoseingholi, Abolfazl Akbari, Javad Yousefi. Predicting metastasis in gastric cancer patients: machine learning-based approachesScientific Reports 2023; 13(1) doi: 10.1038/s41598-023-31272-w
20
Thifhelimbilu Luvhengo, Thulo Molefi, Demetra Demetriou, Rodney Hull, Zodwa Dlamini. Artificial Intelligence and Precision Oncology2023; : 49 doi: 10.1007/978-3-031-21506-3_3
21
Gopika SenthilKumar, Sharadhi Madhusudhana, Madelyn Flitcroft, Salma Sheriff, Samih Thalji, Jennifer Merrill, Callisia N. Clarke, Ugwuji N. Maduekwe, Susan Tsai, Kathleen K. Christians, T. Clark Gamblin, Anai N. Kothari. Automated machine learning (AutoML) can predict 90-day mortality after gastrectomy for cancerScientific Reports 2023; 13(1) doi: 10.1038/s41598-023-37396-3
22
Siqing Jiang, Haojun Gao, Jiajin He, Jiaqi Shi, Yuling Tong, Jian Wu. Machine learning: A non-invasive prediction method for gastric cancer based on a survey of lifestyle behaviorsFrontiers in Artificial Intelligence 2022; 5 doi: 10.3389/frai.2022.956385
23
Yu Yang, Yu-Xuan Li, Ren-Qi Yao, Xiao-Hui Du, Chao Ren. Artificial intelligence in small intestinal diseases: Application and prospectsWorld Journal of Gastroenterology 2021; 27(25): 3734-3747 doi: 10.3748/wjg.v27.i25.3734
24
Sarah El-Nakeep, Mohamed El-Nakeep. Artificial intelligence for cancer detection in upper gastrointestinal endoscopy, current status, and future aspirationsArtificial Intelligence in Gastroenterology 2021; 2(5): 124-132 doi: 10.35712/aig.v2.i5.124
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Shinichi Kinami, Hitoshi Saito, Hiroyuki Takamura. Significance of Lymph Node Metastasis in the Treatment of Gastric Cancer and Current Challenges in Determining the Extent of MetastasisFrontiers in Oncology 2022; 11 doi: 10.3389/fonc.2021.806162
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Kamalrulnizam Bin Abu Bakar, Fatima Tul Zuhra, Babangida Isyaku, Fuad A. Ghaleb. Optimized Identification with Severity Factors of Gastric Cancer for Internet of Medical ThingsComputers, Materials & Continua 2023; 75(1): 785 doi: 10.32604/cmc.2023.034540
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Vangelis D. Karalis. From Current to Future Trends in Pharmaceutical Technology2024; : 215 doi: 10.1016/B978-0-323-91111-5.00006-8
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Miguel Angel Ruiz-Fresneda, Alfonso Gijón, Pablo Morales-Álvarez. Bibliometric analysis of the global scientific production on machine learning applied to different cancer typesEnvironmental Science and Pollution Research 2023; 30(42): 96125 doi: 10.1007/s11356-023-28576-9
29
Guanhua Duan, Yankun Cao, Xiaoxiao Cui, Zhen Li, Xiaoyun Yang, Zhi Liu. SwinDeepLab:Swin Transformer-based DeepLab v3+ for Gland Segmentation2023 16th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics (CISP-BMEI) 2023; : 1 doi: 10.1109/CISP-BMEI60920.2023.10373361
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Hyon Kim, Young Lim, Seung-In Seo, Kyung Lee, Jae Kim, Woon Shin. A Deep Recurrent Neural Network-Based Explainable Prediction Model for Progression from Atrophic Gastritis to Gastric CancerApplied Sciences 2021; 11(13): 6194 doi: 10.3390/app11136194
31
Hira Imad Cheema, Benjamin Tharian, Sumant Inamdar, Mauricio Garcia-Saenz-de-Sicilia, Cem Cengiz. Recent advances in endoscopic management of gastric neoplasmsWorld Journal of Gastrointestinal Endoscopy 2023; 15(5): 319-337 doi: 10.4253/wjge.v15.i5.319
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Benjamin Franc. Cancer Metastasis Through the Lymphovascular System2022; : 775 doi: 10.1007/978-3-030-93084-4_74
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Prabhakaran Mathialagan, Malathy Chidambaranathan. Morphological and Characteristic Analysis of Upper Aero-Digestive Tract Tumour: Revealing Uncovered Facts in Digital Pathology2021 International Conference on Computing, Communication, and Intelligent Systems (ICCCIS) 2021; : 550 doi: 10.1109/ICCCIS51004.2021.9397133
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洪铭 崔. Application of Artificial Intelligence in Gastrointestinal CancerAdvances in Clinical Medicine 2023; 13(03): 3942 doi: 10.12677/ACM.2023.133566
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Yizhi Liang, Zilan Rao, Dongwei Du, Yiwen Wang, Taiyong Fang. Butyrate prevents the migration and invasion, and aerobic glycolysis in gastric cancer via inhibiting Wnt/β‐catenin/c‐Myc signalingDrug Development Research 2023; 84(3): 527 doi: 10.1002/ddr.22043
36
Scott B Minchenberg, Trent Walradt, Jeremy R Glissen Brown. Scoping out the future: The application of artificial intelligence to gastrointestinal endoscopyWorld Journal of Gastrointestinal Oncology 2022; 14(5): 989-1001 doi: 10.4251/wjgo.v14.i5.989
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Maryam Koopaie, Marjan Ghafourian, Soheila Manifar, Shima Younespour, Mansour Davoudi, Sajad Kolahdooz, Mohammad Shirkhoda. Evaluation of CSTB and DMBT1 expression in saliva of gastric cancer patients and controlsBMC Cancer 2022; 22(1) doi: 10.1186/s12885-022-09570-9
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Huang Junjun, Jiang Yujie. Image Recognition and Diagnosis System of Early Gastric Cancer Based on Artificial Intelligence Algorithm2023 3rd Asia-Pacific Conference on Communications Technology and Computer Science (ACCTCS) 2023; : 77 doi: 10.1109/ACCTCS58815.2023.00068
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Yong Liu. Artificial intelligence-assisted endoscopic detection of esophageal neoplasia in early stage: The next step?World Journal of Gastroenterology 2021; 27(14): 1392-1405 doi: 10.3748/wjg.v27.i14.1392
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Emma Briggs, Marc de Kamps, Willie Hamilton, Owen Johnson, Ciarán D. McInerney, Richard D. Neal. Machine Learning for Risk Prediction of Oesophago-Gastric Cancer in Primary Care: Comparison with Existing Risk-Assessment ToolsCancers 2022; 14(20): 5023 doi: 10.3390/cancers14205023
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Huina Ma, Hehua Huang, Chenyu Li, Shasha Li, Juefang Gan, Chunrong Lian, Yanwu Ling. The antidepressive mechanism of Longya Lilium combined with Fluoxetine in mice with depression-like behaviorsnpj Systems Biology and Applications 2024; 10(1) doi: 10.1038/s41540-024-00329-5
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Xiulan Yang, Yudong Zheng, Lian Liu, Jiangrong Huang, Fei Wang, Jie Zhang. Progress on the study of the anticancer effects of artesunate (Review)Oncology Letters 2021; 22(5) doi: 10.3892/ol.2021.13011
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Anil Alpsoy, Aysen Yavuz, Gulsum Ozlem Elpek. Artificial intelligence in pathological evaluation of gastrointestinal cancersArtificial Intelligence in Gastroenterology 2021; 2(6): 141-156 doi: 10.35712/aig.v2.i6.141
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Dusan Popovic, Tijana Glisic, Tomica Milosavljevic, Natasa Panic, Marija Marjanovic-Haljilji, Dragana Mijac, Milica Stojkovic Lalosevic, Jelena Nestorov, Sanja Dragasevic, Predrag Savic, Branka Filipovic. The Importance of Artificial Intelligence in Upper Gastrointestinal EndoscopyDiagnostics 2023; 13(18): 2862 doi: 10.3390/diagnostics13182862
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Harriet Evans, David Snead. Why do errors arise in artificial intelligence diagnostic tools in histopathology and how can we minimize them?Histopathology 2024; 84(2): 279 doi: 10.1111/his.15071
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Ji-Han Qi, Shi-Ling Huang, Shi-Zhu Jin. Novel milestones for early esophageal carcinoma: From bench to bedWorld Journal of Gastrointestinal Oncology 2024; 16(4): 1104-1118 doi: 10.4251/wjgo.v16.i4.1104
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Jasminka Hasic Telalovic, Serena Pillozzi, Rachele Fabbri, Alice Laffi, Daniele Lavacchi, Virginia Rossi, Lorenzo Dreoni, Francesca Spada, Nicola Fazio, Amedeo Amedei, Ernesto Iadanza, Lorenzo Antonuzzo. A Machine Learning Decision Support System (DSS) for Neuroendocrine Tumor Patients Treated with Somatostatin Analog (SSA) TherapyDiagnostics 2021; 11(5): 804 doi: 10.3390/diagnostics11050804
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Hongliu Du, Zehua Dong, Lianlian Wu, Yanxia Li, Jun Liu, Chaijie Luo, Xiaoquan Zeng, Yunchao Deng, Du Cheng, Wenxiu Diao, Yijie Zhu, Xiao Tao, Junxiao Wang, Chenxia Zhang, Honggang Yu. A deep-learning based system using multi-modal data for diagnosing gastric neoplasms in real-time (with video)Gastric Cancer 2023; 26(2): 275 doi: 10.1007/s10120-022-01358-x
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E. Dilaghi, E. Lahner, B. Annibale, G. Esposito. Systematic review and meta-analysis: Artificial intelligence for the diagnosis of gastric precancerous lesions and Helicobacter pylori infectionDigestive and Liver Disease 2022; 54(12): 1630 doi: 10.1016/j.dld.2022.03.007
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Jiahui Wei, Ruiqing Wang, Yiran Lu, Song He, Yu Ding. Flotillin-1 promotes progression and dampens chemosensitivity to cisplatin in gastric cancer via ERK and AKT signaling pathwaysEuropean Journal of Pharmacology 2022; 916: 174631 doi: 10.1016/j.ejphar.2021.174631
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Tao Yan, Pak Kin Wong, Ye-Ying Qin. Deep learning for diagnosis of precancerous lesions in upper gastrointestinal endoscopy: A reviewWorld Journal of Gastroenterology 2021; 27(20): 2531-2544 doi: 10.3748/wjg.v27.i20.2531
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Ryosuke Tonozuka, Ryota Niikura, Takao Itoi. Artificial intelligence for routine esophagogastroduodenoscopy quality monitoring: Is the future right before our eyes?Gastrointestinal Endoscopy 2022; 95(6): 1147 doi: 10.1016/j.gie.2022.02.030
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Mohammad Reza Afrash, Mohsen Shafiee, Hadi Kazemi-Arpanahi. Establishing machine learning models to predict the early risk of gastric cancer based on lifestyle factorsBMC Gastroenterology 2023; 23(1) doi: 10.1186/s12876-022-02626-x
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Yu Xiao, Zhigang Song, Shuangmei Zou, Yan You, Jie Cui, Shuhao Wang, Calvin Ku, Xi Wu, Xiaowei Xue, Wenqi Han, Weixun Zhou. Artificial Intelligence Assisted Topographic Mapping System for Endoscopic Submucosal Dissection SpecimensFrontiers in Medicine 2022; 9 doi: 10.3389/fmed.2022.822731
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Swathikan Chidambaram, Viknesh Sounderajah, Nick Maynard, Sheraz R. Markar. Diagnostic Performance of Artificial Intelligence-Centred Systems in the Diagnosis and Postoperative Surveillance of Upper Gastrointestinal Malignancies Using Computed Tomography Imaging: A Systematic Review and Meta-Analysis of Diagnostic AccuracyAnnals of Surgical Oncology 2022; 29(3): 1977 doi: 10.1245/s10434-021-10882-6
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Maryam Kausar Khan, Muhammad Siddique, Naeem Aslam, Muntazir Hussain Khan, Sara Mukhtar, Bushra Syed. Improvement for Diagnosis of Gastric Cancer from Endoscopic Images using Machine LearningVFAST Transactions on Software Engineering 2022; 10(3): 10 doi: 10.21015/vtse.v10i3.1054
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Oleg Martos, Md Ziaul Hoque, Anja Keskinarkaus, Niko Kemi, Juha Näpänkangas, Maarit Eskuri, Vesa-Matti Pohjanen, Joonas H. Kauppila, Tapio Seppänen. Optimized detection and segmentation of nuclei in gastric cancer images using stain normalization and blurred artifact removalPathology - Research and Practice 2023; 248: 154694 doi: 10.1016/j.prp.2023.154694
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Yang Su, Yanqi Li, Wenshu Chen, Wangshuo Yang, Jichao Qin, Lu Liu. Automated machine learning-based model for predicting benign anastomotic strictures in patients with rectal cancer who have received anterior resectionEuropean Journal of Surgical Oncology 2023; 49(12): 107113 doi: 10.1016/j.ejso.2023.107113
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Lukas Buendgens, Didem Cifci, Narmin Ghaffari Laleh, Marko van Treeck, Maria T. Koenen, Henning W. Zimmermann, Till Herbold, Thomas Joachim Lux, Alexander Hann, Christian Trautwein, Jakob Nikolas Kather. Weakly supervised end-to-end artificial intelligence in gastrointestinal endoscopyScientific Reports 2022; 12(1) doi: 10.1038/s41598-022-08773-1