BPG is committed to discovery and dissemination of knowledge
Cited by in CrossRef
For: Faur AC, Lazar DC, Ghenciu LA. Artificial intelligence as a noninvasive tool for pancreatic cancer prediction and diagnosis. World J Gastroenterol 2023; 29(12): 1811-1823 [PMID: 37032728 DOI: 10.3748/wjg.v29.i12.1811]
URL: https://www.wjgnet.com/1948-9366/full/v29/i12/1811.htm
Number Citing Articles
1
S. I. Panin, V. A. Suvorov, A. V. Zubkov, S. A. Bezborodov, A. A. Panina, N. V. Kovalenko, A. R. Donsckaia, I. G. Shushkova, A. V. Bykov, Ya. A. Marenkov. Artificial intelligence for screening and early diagnosis of pancreatic neoplasms in the context of centralization of the laboratory service in the region.Siberian journal of oncology 2024; 23(3): 124 doi: 10.21294/1814-4861-2024-23-3-124-132
2
Federica Flammia, Roberta Fusco, Sonia Triggiani, Giuseppe Pellegrino, Alfonso Reginelli, Igino Simonetti, Piero Trovato, Sergio Venanzio Setola, Giuseppe Petralia, Antonella Petrillo, Francesco Izzo, Vincenza Granata. Risk Assessment and Radiomics Analysis in Magnetic Resonance Imaging of Pancreatic Intraductal Papillary Mucinous Neoplasms (IPMN)Cancer Control 2024; 31 doi: 10.1177/10732748241263644
3
冠宇 吴. To Compare the Stability of Different Clinical Model Frameworks in the Overall Survival Rate and Specific Survival Rate of Patients with Non-Metastatic Pancreatic Head Cancer, Pancreatic Body Cancer and Pancreatic Tail Cancer Based on Machine LearningAdvances in Clinical Medicine 2023; 13(11): 18150 doi: 10.12677/ACM.2023.13112547
4
Giulia Pacella, Maria Chiara Brunese, Eleonora D’Imperio, Marco Rotondo, Andrea Scacchi, Mattia Carbone, Germano Guerra. Pancreatic Ductal Adenocarcinoma: Update of CT-Based Radiomics Applications in the Pre-Surgical Prediction of the Risk of Post-Operative Fistula, Resectability Status and PrognosisJournal of Clinical Medicine 2023; 12(23): 7380 doi: 10.3390/jcm12237380
5
Xing Ke, Xinyu Cai, Bingxian Bian, Yuanheng Shen, Yunlan Zhou, Wei Liu, Xu Wang, Lisong Shen, Junyao Yang. Predicting early gastric cancer risk using machine learning: A population-based retrospective studyDIGITAL HEALTH 2024; 10 doi: 10.1177/20552076241240905
6
Shamsher A. Pasha, Abdullah Khalid, Todd Levy, Lyudmyla Demyan, Sarah Hartman, Elliot Newman, Matthew J. Weiss, Daniel A. King, Theodoros Zanos, Marcovalerio Melis. Machine learning to predict completion of treatment for pancreatic cancerJournal of Surgical Oncology 2024;  doi: 10.1002/jso.27812
7
Hardik Patel, Theodoros Zanos, D. Brock Hewitt. Deep Learning Applications in Pancreatic CancerCancers 2024; 16(2): 436 doi: 10.3390/cancers16020436
8
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