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For: Ma H, Liu ZX, Zhang JJ, Wu FT, Xu CF, Shen Z, Yu CH, Li YM. Construction of a convolutional neural network classifier developed by computed tomography images for pancreatic cancer diagnosis. World J Gastroenterol 2020; 26(34): 5156-5168 [PMID: 32982116 DOI: 10.3748/wjg.v26.i34.5156]
URL: https://www.wjgnet.com/1007-9327/full/v26/i34/5156.htm
Number Citing Articles
1
H Shafeeq AHMED. BEYOND TRADITIONAL TOOLS: EXPLORING CONVOLUTIONAL NEURAL NETWORKS AS INNOVATIVE PROGNOSTIC MODELS IN PANCREATIC DUCTAL ADENOCARCINOMAArquivos de Gastroenterologia 2024; 61 doi: 10.1590/s0004-2803.24612023-117
2
Gintautas Dzemyda, Olga Kurasova, Viktor Medvedev, Aušra Šubonienė, Aistė Gulla, Artūras Samuilis, Džiugas Jagminas, Kęstutis Strupas. Deep learning‐based aggregate analysis to identify cut‐off points for decision‐making in pancreatic cancer detectionExpert Systems 2024;  doi: 10.1111/exsy.13614
3
Mark Ramaekers, Christiaan G. A. Viviers, Boris V. Janssen, Terese A. E. Hellström, Lotte Ewals, Kasper van der Wulp, Joost Nederend, Igor Jacobs, Jon R. Pluyter, Dimitrios Mavroeidis, Fons van der Sommen, Marc G. Besselink, Misha D. P. Luyer. Computer-Aided Detection for Pancreatic Cancer Diagnosis: Radiological Challenges and Future DirectionsJournal of Clinical Medicine 2023; 12(13): 4209 doi: 10.3390/jcm12134209
4
Chunzhi Meng, Hongyi Li, Chen Chen, Wei Wu, Jing Gao, Yining Lai, Mila Ka, Min Zhu, Xiaoyi Lv, Fangfang Chen, Cheng Chen. Serum Raman spectroscopy combined with Gaussian—convolutional neural network models to quickly detect liver cancer patientsSpectroscopy Letters 2022; 55(2): 79 doi: 10.1080/00387010.2022.2027988
5
Guohua Zhao, Xi Chen, Mengying Zhu, Yang Liu, Yue Wang. Exploring the application and future outlook of Artificial intelligence in pancreatic cancerFrontiers in Oncology 2024; 14 doi: 10.3389/fonc.2024.1345810
6
Maxime Barat, Guillaume Chassagnon, Anthony Dohan, Sébastien Gaujoux, Romain Coriat, Christine Hoeffel, Christophe Cassinotto, Philippe Soyer. Artificial intelligence: a critical review of current applications in pancreatic imagingJapanese Journal of Radiology 2021; 39(6): 514 doi: 10.1007/s11604-021-01098-5
7
Jiaqi Qu, Xiang Xiao, Xunbin Wei, Xiaohua Qian. A causality-inspired generalized model for automated pancreatic cancer diagnosisMedical Image Analysis 2024; 94: 103154 doi: 10.1016/j.media.2024.103154
8
Minjae Kim, Sunghoi Hong. Integrating Artificial Intelligence to Biomedical Science: New Applications for Innovative Stem Cell Research and Drug DevelopmentTechnologies 2024; 12(7): 95 doi: 10.3390/technologies12070095
9
Natália Alves, Megan Schuurmans, Geke Litjens, Joeran S. Bosma, John Hermans, Henkjan Huisman. Fully Automatic Deep Learning Framework for Pancreatic Ductal Adenocarcinoma Detection on Computed TomographyCancers 2022; 14(2): 376 doi: 10.3390/cancers14020376
10
Kenneth Weicong Lin, Tiing Leong Ang, James Weiquan Li. Role of artificial intelligence in early detection and screening for pancreatic adenocarcinomaArtificial Intelligence in Medical Imaging 2022; 3(2): 21-32 doi: 10.35711/aimi.v3.i2.21
11
Hoang Quang Huy, Ngo Tien Dat, Dinh Nghia Hiep, Nguyen Ngoc Tram, Tran Anh Vu, Pham Thi Viet Huong. Intelligent Systems and NetworksLecture Notes in Networks and Systems 2023; 752: 66 doi: 10.1007/978-981-99-4725-6_10
12
Jasmine Chhikara, Nidhi Goel, Neeru Rathee. Integrating expert guidance with gradual moment approximation (GMAp)-enhanced transfer learning for improved pancreatic cancer classificationNeural Computing and Applications 2024;  doi: 10.1007/s00521-024-10521-7
13
Deepak Painuli, Suyash Bhardwaj, Utku Köse. Advances and Applications of Artificial Intelligence & Machine LearningLecture Notes in Electrical Engineering 2023; 1078: 685 doi: 10.1007/978-981-99-5974-7_55
14
Florbela Tavares, Gilberto Rosa, Inês Henriques, Nelson Pacheco Rocha. Good Practices and New Perspectives in Information Systems and TechnologiesLecture Notes in Networks and Systems 2024; 986: 129 doi: 10.1007/978-3-031-60218-4_13
15
Kaiwen Chen, Chunyu Zhang, Chengjian Qiu, Yuqing Song, Anthony Miller, Lu Liu, Imran Ul Haq, Zhe Liu. Neural Information ProcessingLecture Notes in Computer Science 2024; 14449: 564 doi: 10.1007/978-981-99-8067-3_42
16
José S Enriquez, Yan Chu, Shivanand Pudakalakatti, Kang Lin Hsieh, Duncan Salmon, Prasanta Dutta, Niki Zacharias Millward, Eugene Lurie, Steven Millward, Florencia McAllister, Anirban Maitra, Subrata Sen, Ann Killary, Jian Zhang, Xiaoqian Jiang, Pratip K Bhattacharya, Shayan Shams. Hyperpolarized Magnetic Resonance and Artificial Intelligence: Frontiers of Imaging in Pancreatic CancerJMIR Medical Informatics 2021; 9(6): e26601 doi: 10.2196/26601
17
Maxime Barat, Ugo Marchese, Anna Pellat, Anthony Dohan, Romain Coriat, Christine Hoeffel, Elliot K. Fishman, Christophe Cassinotto, Linda Chu, Philippe Soyer. Imaging of Pancreatic Ductal Adenocarcinoma: An Update on Recent AdvancesCanadian Association of Radiologists Journal 2023; 74(2): 351 doi: 10.1177/08465371221124927
18
Passisd Laoveeravat, Priya R Abhyankar, Aaron R Brenner, Moamen M Gabr, Fadlallah G Habr, Amporn Atsawarungruangkit. Artificial intelligence for pancreatic cancer detection: Recent development and future direction Artificial Intelligence in Gastroenterology 2021; 2(2): 56-68 doi: 10.35712/aig.v2.i2.56
19
Megan Schuurmans, Natália Alves, Pierpaolo Vendittelli, Henkjan Huisman, John Hermans. Setting the Research Agenda for Clinical Artificial Intelligence in Pancreatic Adenocarcinoma ImagingCancers 2022; 14(14): 3498 doi: 10.3390/cancers14143498
20
Jiaqi Qu, Xunbin Wei, Xiaohua Qian. Generalized pancreatic cancer diagnosis via multiple instance learning and anatomically-guided shape normalizationMedical Image Analysis 2023; 86: 102774 doi: 10.1016/j.media.2023.102774
21
Jasmine Chhikara, Nidhi Goel, Neeru Rathee. Deep Learning Techniques for Pancreatic Cancer Analysis: A Systematic Review and Implantation PrerequisitesProcedia Computer Science 2024; 235: 3118 doi: 10.1016/j.procs.2024.04.295
22
Juan Li, Yanru Li, Shuai Chen, Weili Duan, Xue Kong, Yunshan Wang, Lianqun Zhou, Peilong Li, Chengpeng Zhang, Lutao Du, Chuanxin Wang. Highly Sensitive Exosome Detection for Early Diagnosis of Pancreatic Cancer Using Immunoassay Based on Hierarchical Surface‐Enhanced Raman Scattering SubstrateSmall Methods 2022; 6(6) doi: 10.1002/smtd.202200154
23
Jasmine Chhikara, Nidhi Goel, Neeru Rathee. Pancreatic Carcinoma Detection with Publicly available Radiological Images: A Systematic Analysis2022 10th International Conference on Reliability, Infocom Technologies and Optimization (Trends and Future Directions) (ICRITO) 2022; : 1 doi: 10.1109/ICRITO56286.2022.9964991
24
Cristian Anghel, Mugur Cristian Grasu, Denisa Andreea Anghel, Gina-Ionela Rusu-Munteanu, Radu Lucian Dumitru, Ioana Gabriela Lupescu. Pancreatic Adenocarcinoma: Imaging Modalities and the Role of Artificial Intelligence in Analyzing CT and MRI ImagesDiagnostics 2024; 14(4): 438 doi: 10.3390/diagnostics14040438
25
Kiersten Preuss, Nate Thach, Xiaoying Liang, Michael Baine, Justin Chen, Chi Zhang, Huijing Du, Hongfeng Yu, Chi Lin, Michael A. Hollingsworth, Dandan Zheng. Using Quantitative Imaging for Personalized Medicine in Pancreatic Cancer: A Review of Radiomics and Deep Learning ApplicationsCancers 2022; 14(7): 1654 doi: 10.3390/cancers14071654
26
Rasha Abu-Khudir, Noor Hafsa, Badr E. Badr. Identifying Effective Biomarkers for Accurate Pancreatic Cancer Prognosis Using Statistical Machine LearningDiagnostics 2023; 13(19): 3091 doi: 10.3390/diagnostics13193091
27
Ajanthaa Lakkshmanan, C. Anbu Ananth, S. Tiroumalmouroughane. Multi-objective Metaheuristics with Intelligent Deep Learning Model for Pancreatic Tumor DiagnosisJournal of Intelligent & Fuzzy Systems 2022; 43(5): 6793 doi: 10.3233/JIFS-221171
28
Yan-Jie Shi, Hai-Tao Zhu, Xiao-Ting Li, Xiao-Yan Zhang, Yu-Liang Liu, Yi-Yuan Wei, Ying-Shi Sun. Histogram array and convolutional neural network of DWI for differentiating pancreatic ductal adenocarcinomas from solid pseudopapillary neoplasms and neuroendocrine neoplasmsClinical Imaging 2023; 96: 15 doi: 10.1016/j.clinimag.2023.01.008
29
Krzysztof Szymoński, Katarzyna Skirlińska-Nosek, Ewelina Lipiec, Kamila Sofińska, Michał Czaja, Natalia Wilkosz, Matylda Krupa, Filip Wanat, Magdalena Ulatowska-Białas, Dariusz Adamek. Combined analytical approach empowers precise spectroscopic interpretation of subcellular components of pancreatic cancer cellsAnalytical and Bioanalytical Chemistry 2023; 415(29-30): 7281 doi: 10.1007/s00216-023-04997-w
30
Ajanthaa Lakkshmanan, C. Anbu Ananth, S. Tiroumalmouroughane S. Tiroumalmouroughane. An automated deep learning based pancreatic tumor diagnosis and classification model using computed tomography imagesInternational Journal of Intelligent Computing and Cybernetics 2022; 15(3): 454 doi: 10.1108/IJICC-09-2021-0212
31
Maha M. Althobaiti, Ahmed Almulihi, Amal Adnan Ashour, Romany F. Mansour, Deepak Gupta, Deepak Kumar Jain. Design of Optimal Deep Learning-Based Pancreatic Tumor and Nontumor Classification Model Using Computed Tomography ScansJournal of Healthcare Engineering 2022; 2022: 1 doi: 10.1155/2022/2872461
32
Thanaporn Viriyasaranon, Sang Myung Woo, Jang-Hwan Choi. Unsupervised Visual Representation Learning Based on Segmentation of Geometric Pseudo-Shapes for Transformer-Based Medical TasksIEEE Journal of Biomedical and Health Informatics 2023; 27(4): 2003 doi: 10.1109/JBHI.2023.3237596
33
Chaithanyadas Kanady Vishnudas, G. R. Gnana King. Computer-aided diagnosis for early detection and staging of human pancreatic tumors using an optimized 3D CNN on computed tomographyMultimedia Systems 2023; 29(5): 2689 doi: 10.1007/s00530-023-01146-2
34
Rares Ilie Orzan, Delia Santa, Noemi Lorenzovici, Thomas Andrei Zareczky, Cristina Pojoga, Renata Agoston, Eva-Henrietta Dulf, Andrada Seicean. Deep Learning in Endoscopic Ultrasound: A Breakthrough in Detecting Distal CholangiocarcinomaCancers 2024; 16(22): 3792 doi: 10.3390/cancers16223792
35
Khurram Hussain, Yuanqing Xia, Ghulam Abbas, Ameer Onaizah. Optimized pancreatic tumor imaging diagnosis using deep neural networkAlexandria Engineering Journal 2024; 108: 387 doi: 10.1016/j.aej.2024.07.124
36
Christiaan Viviers, Mark Ramaekers, Amaan Valiuddin, Terese Hellström, Nick Tasios, John van der Ven, Igor Jacobs, Lotte Ewals, Joost Nederend, Peter de With, Misha Luyer, Fons van der Sommen. Segmentation-based Assessment of Tumor-Vessel Involvement for Surgical Resectability Prediction of Pancreatic Ductal Adenocarcinoma2023 IEEE/CVF International Conference on Computer Vision Workshops (ICCVW) 2023; : 2413 doi: 10.1109/ICCVW60793.2023.00256
37
M. G. Dinesh, Nebojsa Bacanin, S. S. Askar, Mohamed Abouhawwash. Diagnostic ability of deep learning in detection of pancreatic tumourScientific Reports 2023; 13(1) doi: 10.1038/s41598-023-36886-8
38
Cai Wang, Pengyi Yu, Haicheng Zhang, Xiao Han, Zheying Song, Guibin Zheng, Guangkuo Wang, Haitao Zheng, Ning Mao, Xicheng Song. Artificial intelligence–based prediction of cervical lymph node metastasis in papillary thyroid cancer with CTEuropean Radiology 2023; 33(10): 6828 doi: 10.1007/s00330-023-09700-2
39
Hiromitsu Hayashi, Norio Uemura, Kazuki Matsumura, Liu Zhao, Hiroki Sato, Yuta Shiraishi, Yo-ichi Yamashita, Hideo Baba. Recent advances in artificial intelligence for pancreatic ductal adenocarcinomaWorld Journal of Gastroenterology 2021; 27(43): 7480-7496 doi: 10.3748/wjg.v27.i43.7480
40
Julia Arribas Anta, Iván Martínez-Ballestero, Daniel Eiroa, Javier García, Júlia Rodríguez-Comas. Artificial intelligence for the detection of pancreatic lesionsInternational Journal of Computer Assisted Radiology and Surgery 2022; 17(10): 1855 doi: 10.1007/s11548-022-02706-z
41
Koteswaramma Dodda, G. Muneeswari. IANFIS: a machine learning–based optimized technique for the classification and segmentation of pancreatic cancerResearch on Biomedical Engineering 2024; 40(2): 373 doi: 10.1007/s42600-024-00352-9
42
Heng Wang, Zhongyi Wu, Fei Wang, Wenting Wei, Kezhen Wei, Zhaobang Liu. MAFF: Multi-scale and self-adaptive attention feature fusion network for pancreatic lesion detection in PET / CT imagesProceedings of the 2022 6th International Conference on Electronic Information Technology and Computer Engineering 2022; : 1412 doi: 10.1145/3573428.3573678
43
K. V. Chaithanyadas, G. R. Gnana King. Computational Vision and Bio-Inspired ComputingAdvances in Intelligent Systems and Computing 2023; 1439: 289 doi: 10.1007/978-981-19-9819-5_22
44
Thavavel Vaiyapuri, Ashit Kumar Dutta, I. S. Hephzi Punithavathi, P. Duraipandy, Saud S. Alotaibi, Hadeel Alsolai, Abdullah Mohamed, Hany Mahgoub. Intelligent Deep-Learning-Enabled Decision-Making Medical System for Pancreatic Tumor Classification on CT ImagesHealthcare 2022; 10(4): 677 doi: 10.3390/healthcare10040677
45
Linda C. Chu, Elliot K. Fishman. The Pancreas2023; : 680 doi: 10.1002/9781119876007.ch88
46
Hari Mohan Rai, Joon Yoo, Abdul Razaque. Comparative analysis of machine learning and deep learning models for improved cancer detection: A comprehensive review of recent advancements in diagnostic techniquesExpert Systems with Applications 2024; 255: 124838 doi: 10.1016/j.eswa.2024.124838
47
Bahrudeen Shahul Hameed, Uma Maheswari Krishnan. Artificial Intelligence-Driven Diagnosis of Pancreatic CancerCancers 2022; 14(21): 5382 doi: 10.3390/cancers14215382
48
Shyamapada Mandal, Keerthiveena Balraj, Hariprasad Kodamana, Chetan Arora, Julie M. Clark, David S. Kwon, Anurag S. Rathore. Weakly supervised large-scale pancreatic cancer detection using multi-instance learningFrontiers in Oncology 2024; 14 doi: 10.3389/fonc.2024.1362850