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For: Lin Q, Ji Y, Chen Y, Sun H, Yang D, Chen A, Chen T, Zhang XM. Radiomics model of contrast‐enhanced MRI for early prediction of acute pancreatitis severity. J Magn Reson Imaging 2019;51:397-406. [DOI: 10.1002/jmri.26798] [Cited by in Crossref: 18] [Cited by in F6Publishing: 18] [Article Influence: 4.5] [Reference Citation Analysis]
Number Citing Articles
1 Song LJ, Xiao B. Medical imaging for pancreatic diseases: Prediction of severe acute pancreatitis complicated with acute respiratory distress syndrome. World J Gastroenterol 2022; 28(44): 6206-6212 [DOI: 10.3748/wjg.v28.i44.6206] [Reference Citation Analysis]
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3 Zhong J, Hu Y, Xing Y, Ge X, Ding D, Zhang H, Yao W. A systematic review of radiomics in pancreatitis: applying the evidence level rating tool for promoting clinical transferability. Insights Imaging 2022;13. [DOI: 10.1186/s13244-022-01279-4] [Cited by in F6Publishing: 1] [Reference Citation Analysis]
4 Laino ME, Ammirabile A, Lofino L, Mannelli L, Fiz F, Francone M, Chiti A, Saba L, Orlandi MA, Savevski V. Artificial Intelligence Applied to Pancreatic Imaging: A Narrative Review. Healthcare 2022;10:1511. [DOI: 10.3390/healthcare10081511] [Cited by in Crossref: 1] [Cited by in F6Publishing: 1] [Article Influence: 1.0] [Reference Citation Analysis]
5 Zhou Y, Han F, Shi XL, Zhang JX, Li GY, Yuan CC, Lu GT, Hu LH, Pan JJ, Xiao WM, Yao GH. Prediction of the severity of acute pancreatitis using machine learning models. Postgrad Med 2022. [PMID: 35801388 DOI: 10.1080/00325481.2022.2099193] [Reference Citation Analysis]
6 Yan G, Yan G, Li H, Liang H, Peng C, Bhetuwal A, Mcclure MA, Li Y, Yang G, Li Y, Zhao L, Fan X. Radiomics and Its Applications and Progress in Pancreatitis: A Current State of the Art Review. Front Med 2022;9:922299. [DOI: 10.3389/fmed.2022.922299] [Reference Citation Analysis]
7 Liu Y, Gu M, Liu L, Cui L, Xing A. CT Image Features Based on the Reconstruction Algorithm for Continuous Blood Purification Combined with Nursing Intervention in the Treatment of Severe Acute Pancreatitis. Contrast Media Mol Imaging 2022;2022:2622316. [PMID: 35414803 DOI: 10.1155/2022/2622316] [Reference Citation Analysis]
8 Abunahel BM, Pontre B, Ko J, Petrov MS. Towards developing a robust radiomics signature in diffuse diseases of the pancreas: Accuracy and stability of features derived from T1-weighted magnetic resonance imaging. Journal of Medical Imaging and Radiation Sciences 2022. [DOI: 10.1016/j.jmir.2022.04.002] [Cited by in Crossref: 1] [Cited by in F6Publishing: 1] [Article Influence: 1.0] [Reference Citation Analysis]
9 Hu Y, Liu N, Tang L, Liu Q, Pan K, Lei L, Huang X. Three-Dimensional Radiomics Features of Magnetic Resonance T2-Weighted Imaging Combined With Clinical Characteristics to Predict the Recurrence of Acute Pancreatitis. Front Med 2022;9:777368. [DOI: 10.3389/fmed.2022.777368] [Cited by in Crossref: 1] [Cited by in F6Publishing: 1] [Article Influence: 1.0] [Reference Citation Analysis]
10 Zhou Y, Ge YT, Shi XL, Wu KY, Chen WW, Ding YB, Xiao WM, Wang D, Lu GT, Hu LH. Machine learning predictive models for acute pancreatitis: A systematic review. Int J Med Inform 2022;157:104641. [PMID: 34785488 DOI: 10.1016/j.ijmedinf.2021.104641] [Cited by in Crossref: 7] [Cited by in F6Publishing: 8] [Article Influence: 3.5] [Reference Citation Analysis]
11 Zhou T, Xie CL, Chen Y, Deng Y, Wu JL, Liang R, Yang GD, Zhang XM. Magnetic Resonance Imaging-Based Radiomics Models to Predict Early Extrapancreatic Necrosis in Acute Pancreatitis. Pancreas 2021;50:1368-75. [PMID: 35041335 DOI: 10.1097/MPA.0000000000001935] [Cited by in Crossref: 3] [Cited by in F6Publishing: 3] [Article Influence: 1.5] [Reference Citation Analysis]
12 Wan T, Wu C, Meng M, Liu T, Li C, Ma J, Qin Z. Radiomic Features on Multiparametric MRI for Preoperative Evaluation of Pituitary Macroadenomas Consistency: Preliminary Findings. J Magn Reson Imaging 2021. [PMID: 34549842 DOI: 10.1002/jmri.27930] [Cited by in Crossref: 1] [Cited by in F6Publishing: 1] [Article Influence: 0.5] [Reference Citation Analysis]
13 Ong Y, Shelat VG. Ranson score to stratify severity in Acute Pancreatitis remains valid - Old is gold. Expert Rev Gastroenterol Hepatol 2021;15:865-77. [PMID: 33944648 DOI: 10.1080/17474124.2021.1924058] [Cited by in Crossref: 10] [Cited by in F6Publishing: 10] [Article Influence: 5.0] [Reference Citation Analysis]
14 Wang Y, Liu K, Xie X, Song B. Potential role of imaging for assessing acute pancreatitis-induced acute kidney injury. Br J Radiol 2021;94:20200802. [PMID: 33237803 DOI: 10.1259/bjr.20200802] [Cited by in Crossref: 2] [Cited by in F6Publishing: 2] [Article Influence: 1.0] [Reference Citation Analysis]
15 Liu S, Li H, Zheng Q, Yang L, Duan M, Feng X, Li F, Huang L, Zhou F. Survival Time Prediction of Breast Cancer Patients Using Feature Selection Algorithm Crystall. IEEE Access 2021;9:24433-24445. [DOI: 10.1109/access.2021.3054823] [Cited by in Crossref: 1] [Cited by in F6Publishing: 1] [Article Influence: 0.5] [Reference Citation Analysis]
16 Wu H, Han X, Wang Z, Mo L, Liu W, Guo Y, Wei X, Jiang X. Prediction of the Ki-67 marker index in hepatocellular carcinoma based on CT radiomics features.Phys Med Biol. 2020;65:235048. [PMID: 32756021 DOI: 10.1088/1361-6560/abac9c] [Cited by in Crossref: 8] [Cited by in F6Publishing: 10] [Article Influence: 2.7] [Reference Citation Analysis]
17 Abunahel BM, Pontre B, Kumar H, Petrov MS. Pancreas image mining: a systematic review of radiomics. Eur Radiol 2021;31:3447-67. [PMID: 33151391 DOI: 10.1007/s00330-020-07376-6] [Cited by in Crossref: 27] [Cited by in F6Publishing: 34] [Article Influence: 9.0] [Reference Citation Analysis]
18 Ghandili S, Shayesteh S, Fouladi DF, Blanco A, Chu LC. Emerging imaging techniques for acute pancreatitis. Abdom Radiol (NY) 2020;45:1299-307. [PMID: 31428811 DOI: 10.1007/s00261-019-02192-z] [Cited by in Crossref: 6] [Cited by in F6Publishing: 4] [Article Influence: 2.0] [Reference Citation Analysis]