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For: Hofmeister J, Bernava G, Rosi A, Vargas MI, Carrera E, Montet X, Burgermeister S, Poletti PA, Platon A, Lovblad KO, Machi P. Clot-Based Radiomics Predict a Mechanical Thrombectomy Strategy for Successful Recanalization in Acute Ischemic Stroke. Stroke 2020;51:2488-94. [PMID: 32684141 DOI: 10.1161/STROKEAHA.120.030334] [Cited by in Crossref: 30] [Cited by in F6Publishing: 30] [Article Influence: 15.0] [Reference Citation Analysis]
Number Citing Articles
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2 Zeng M, Oakden-rayner L, Bird A, Smith L, Wu Z, Scroop R, Kleinig T, Jannes J, Jenkinson M, Palmer LJ. Pre-thrombectomy prognostic prediction of large-vessel ischemic stroke using machine learning: A systematic review and meta-analysis. Front Neurol 2022;13:945813. [DOI: 10.3389/fneur.2022.945813] [Reference Citation Analysis]
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6 Sui H, Wu J, Zhou Q, Liu L, Lv Z, Zhang X, Yang H, Shen Y, Liao S, Shi F, Mo Z. Nomograms predict prognosis and hospitalization time using non-contrast CT and CT perfusion in patients with ischemic stroke. Front Neurosci 2022;16:912287. [DOI: 10.3389/fnins.2022.912287] [Cited by in Crossref: 1] [Cited by in F6Publishing: 1] [Article Influence: 1.0] [Reference Citation Analysis]
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8 Dumitriu Lagrange D, Bernava G, Reymond P, Wanke I, Vargas MI, Machi P, Lövblad K. A high resolution scanning electron microscopy analysis of intracranial thrombi embedded along the stent retrievers. Sci Rep 2022;12. [DOI: 10.1038/s41598-022-11830-4] [Cited by in F6Publishing: 1] [Reference Citation Analysis]
9 Wang Y, Zhu J, Zhao J, Li W, Zhang X, Meng X, Chen T, Li M, Ye M, Hu R, Dou S, Hao H, Zhao X, Wu X, Hu W, Li C, Fan X, Jiang L, Lu X, Yan F. Deep Learning-Enabled Clinically Applicable CT Planbox for Stroke With High Accuracy and Repeatability. Front Neurol 2022;13:755492. [DOI: 10.3389/fneur.2022.755492] [Reference Citation Analysis]
10 Christiansen SD, Liu J, Bres Bullrich M, Sharma M, Pandey SK, Boulton M, Fridman S, Sposato LA, Drangova M. Ex Vivo Thrombus Magnetic Resonance Imaging Features and Patient Clinical Data Enable Prediction of Acute Ischemic Stroke Cause. SVIN 2022;2. [DOI: 10.1161/svin.121.000157] [Reference Citation Analysis]
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12 Werdiger F, Bivard A, Parsons M. Artificial Intelligence in Acute Ischemic Stroke. Artificial Intelligence in Medicine 2022. [DOI: 10.1007/978-3-030-64573-1_287] [Reference Citation Analysis]
13 LaGrange DD, Wanke I, Machi P, Bernava G, Vargas M, Botta D, Berberat J, Muster M, Platon A, Poletti PA, Lövblad KO. Multimodality Characterization of the Clot in Acute Stroke. Front Neurol 2021;12:760148. [PMID: 34970209 DOI: 10.3389/fneur.2021.760148] [Reference Citation Analysis]
14 Shlobin NA, Baig AA, Waqas M, Patel TR, Dossani RH, Wilson No Degree M, Cappuzzo JM, Siddiqui AH, Tutino VM, Levy EI. Artificial Intelligence for Large Vessel Occlusion Stroke: A Systematic Review. World Neurosurg 2021:S1878-8750(21)01846-5. [PMID: 34896351 DOI: 10.1016/j.wneu.2021.12.004] [Cited by in Crossref: 1] [Cited by in F6Publishing: 1] [Article Influence: 1.0] [Reference Citation Analysis]
15 Sotoudeh H, Sarrami AH, Roberson GH, Shafaat O, Sadaatpour Z, Rezaei A, Choudhary G, Singhal A, Sotoudeh E, Tanwar M. Emerging Applications of Radiomics in Neurological Disorders: A Review. Cureus 2021;13:e20080. [PMID: 34987940 DOI: 10.7759/cureus.20080] [Cited by in Crossref: 1] [Cited by in F6Publishing: 2] [Article Influence: 1.0] [Reference Citation Analysis]
16 Zhang Y, Chen C, Huang W, Cheng Y, Teng Y, Zhang L, Xu J. Machine Learning-Based Radiomics of the Optic Chiasm Predict Visual Outcome Following Pituitary Adenoma Surgery. J Pers Med 2021;11:991. [PMID: 34683132 DOI: 10.3390/jpm11100991] [Reference Citation Analysis]
17 Zhang H, Polson J, Nael K, Salamon N, Yoo B, Speier W, Arnold C. A Machine Learning Approach to Predict Acute Ischemic Stroke Thrombectomy Reperfusion using Discriminative MR Image Features. 2021 IEEE EMBS International Conference on Biomedical and Health Informatics (BHI) 2021. [DOI: 10.1109/bhi50953.2021.9508597] [Reference Citation Analysis]
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19 CT-Merkmale von Thromben bei Schlaganfällen unterschiedlicher Ursache. Radiologie up2date 2021;21:101-102. [DOI: 10.1055/a-1389-0056] [Reference Citation Analysis]
20 Zeleňák K, Krajina A, Meyer L, Fiehler J, Esmint Artificial Intelligence And Robotics Ad Hoc Committee, Behme D, Bulja D, Caroff J, Chotai AA, Da Ros V, Gentric JC, Hofmeister J, Kass-Hout O, Kocatürk Ö, Lynch J, Pearson E, Vukasinovic I. How to Improve the Management of Acute Ischemic Stroke by Modern Technologies, Artificial Intelligence, and New Treatment Methods. Life (Basel) 2021;11:488. [PMID: 34072071 DOI: 10.3390/life11060488] [Cited by in Crossref: 6] [Cited by in F6Publishing: 7] [Article Influence: 6.0] [Reference Citation Analysis]
21 Sarioglu O, Sarioglu FC, Capar AE, Sokmez DFB, Topkaya P, Belet U. The role of CT texture analysis in predicting the clinical outcomes of acute ischemic stroke patients undergoing mechanical thrombectomy. Eur Radiol 2021;31:6105-15. [PMID: 33559698 DOI: 10.1007/s00330-021-07720-4] [Cited by in Crossref: 5] [Cited by in F6Publishing: 5] [Article Influence: 5.0] [Reference Citation Analysis]
22 Werdiger F, Bivard A, Parsons M. Artificial Intelligence in Acute Ischemic Stroke. Artificial Intelligence in Medicine 2021. [DOI: 10.1007/978-3-030-58080-3_287-1] [Reference Citation Analysis]