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For: Starke S, Leger S, Zwanenburg A, Leger K, Lohaus F, Linge A, Schreiber A, Kalinauskaite G, Tinhofer I, Guberina N, Guberina M, Balermpas P, von der Grün J, Ganswindt U, Belka C, Peeken JC, Combs SE, Boeke S, Zips D, Richter C, Troost EGC, Krause M, Baumann M, Löck S. 2D and 3D convolutional neural networks for outcome modelling of locally advanced head and neck squamous cell carcinoma. Sci Rep 2020;10:15625. [PMID: 32973220 DOI: 10.1038/s41598-020-70542-9] [Cited by in Crossref: 6] [Cited by in F6Publishing: 4] [Article Influence: 3.0] [Reference Citation Analysis]
Number Citing Articles
1 Shailesh S, Judy M. Understanding Dance Semantics using Spatio-Temporal Features Coupled GRU Networks. Entertainment Computing 2022. [DOI: 10.1016/j.entcom.2022.100484] [Reference Citation Analysis]
2 Lombardo E, Kurz C, Marschner S, Avanzo M, Gagliardi V, Fanetti G, Franchin G, Stancanello J, Corradini S, Niyazi M, Belka C, Parodi K, Riboldi M, Landry G. Distant metastasis time to event analysis with CNNs in independent head and neck cancer cohorts. Sci Rep 2021;11:6418. [PMID: 33742070 DOI: 10.1038/s41598-021-85671-y] [Cited by in Crossref: 4] [Cited by in F6Publishing: 1] [Article Influence: 4.0] [Reference Citation Analysis]
3 Tomita H, Kobayashi T, Takaya E, Mishiro S, Hirahara D, Fujikawa A, Kurihara Y, Mimura H, Kobayashi Y. Deep learning approach of diffusion-weighted imaging as an outcome predictor in laryngeal and hypopharyngeal cancer patients with radiotherapy-related curative treatment: a preliminary study. Eur Radiol 2022. [PMID: 35201406 DOI: 10.1007/s00330-022-08630-9] [Reference Citation Analysis]
4 Siriapisith T, Kusakunniran W, Haddawy P. A 3D deep learning approach to epicardial fat segmentation in non-contrast and post-contrast cardiac CT images. PeerJ Comput Sci 2021;7:e806. [PMID: 34977354 DOI: 10.7717/peerj-cs.806] [Reference Citation Analysis]
5 Bousabarah K, Blanck O, Temming S, Wilhelm ML, Hoevels M, Baus WW, Ruess D, Visser-Vandewalle V, Ruge MI, Treuer H, Kocher M. Radiomics for prediction of radiation-induced lung injury and oncologic outcome after robotic stereotactic body radiotherapy of lung cancer: results from two independent institutions. Radiat Oncol 2021;16:74. [PMID: 33863358 DOI: 10.1186/s13014-021-01805-6] [Reference Citation Analysis]
6 Marschner SN, Lombardo E, Minibek L, Holzgreve A, Kaiser L, Albert NL, Kurz C, Riboldi M, Späth R, Baumeister P, Niyazi M, Belka C, Corradini S, Landry G, Walter F. Risk Stratification Using 18F-FDG PET/CT and Artificial Neural Networks in Head and Neck Cancer Patients Undergoing Radiotherapy. Diagnostics (Basel) 2021;11:1581. [PMID: 34573924 DOI: 10.3390/diagnostics11091581] [Reference Citation Analysis]
7 Anandanadarajah N, Chu CH, Loganantharaj R. An integrated deep learning and dynamic programming method for predicting tumor suppressor genes, oncogenes, and fusion from PDB structures. Comput Biol Med 2021;133:104323. [PMID: 33934067 DOI: 10.1016/j.compbiomed.2021.104323] [Reference Citation Analysis]
8 Sager P, Näf L, Vu E, Fischer T, Putora PM, Ehret F, Fürweger C, Schröder C, Förster R, Zwahlen DR, Muacevic A, Windisch P. Convolutional Neural Networks for Classifying Laterality of Vestibular Schwannomas on Single MRI Slices-A Feasibility Study. Diagnostics (Basel) 2021;11:1676. [PMID: 34574017 DOI: 10.3390/diagnostics11091676] [Reference Citation Analysis]
9 Wan Y, Yang P, Xu L, Yang J, Luo C, Wang J, Chen F, Wu Y, Lu Y, Ruan D, Niu T. Radiomics analysis combining unsupervised learning and handcrafted features: A multiple-disease study. Med Phys 2021;48:7003-15. [PMID: 34453332 DOI: 10.1002/mp.15199] [Reference Citation Analysis]
10 Navarro F, Dapper H, Asadpour R, Knebel C, Spraker MB, Schwarze V, Schaub SK, Mayr NA, Specht K, Woodruff HC, Lambin P, Gersing AS, Nyflot MJ, Menze BH, Combs SE, Peeken JC. Development and External Validation of Deep-Learning-Based Tumor Grading Models in Soft-Tissue Sarcoma Patients Using MR Imaging. Cancers (Basel) 2021;13:2866. [PMID: 34201251 DOI: 10.3390/cancers13122866] [Cited by in F6Publishing: 1] [Reference Citation Analysis]
11 Volpe S, Pepa M, Zaffaroni M, Bellerba F, Santamaria R, Marvaso G, Isaksson LJ, Gandini S, Starzyńska A, Leonardi MC, Orecchia R, Alterio D, Jereczek-Fossa BA. Machine Learning for Head and Neck Cancer: A Safe Bet?-A Clinically Oriented Systematic Review for the Radiation Oncologist. Front Oncol 2021;11:772663. [PMID: 34869010 DOI: 10.3389/fonc.2021.772663] [Reference Citation Analysis]