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Cited by in F6Publishing
For: Avanzo M, Pirrone G, Vinante L, Caroli A, Stancanello J, Drigo A, Massarut S, Mileto M, Urbani M, Trovo M, El Naqa I, De Paoli A, Sartor G. Electron Density and Biologically Effective Dose (BED) Radiomics-Based Machine Learning Models to Predict Late Radiation-Induced Subcutaneous Fibrosis. Front Oncol 2020;10:490. [PMID: 32373520 DOI: 10.3389/fonc.2020.00490] [Cited by in Crossref: 6] [Cited by in F6Publishing: 9] [Article Influence: 3.0] [Reference Citation Analysis]
Number Citing Articles
1 Zhang X, Zhang B, Wang B, Zhang F. Automatic Prediction of T2/T3 Staging of Rectal Cancer Based on Radiomics and Machine Learning. Big Data Research 2022. [DOI: 10.1016/j.bdr.2022.100346] [Reference Citation Analysis]
2 Bettinelli A, Marturano F, Avanzo M, Loi E, Menghi E, Mezzenga E, Pirrone G, Sarnelli A, Strigari L, Strolin S, Paiusco M. A Novel Benchmarking Approach to Assess the Agreement among Radiomic Tools. Radiology 2022;:211604. [PMID: 35230182 DOI: 10.1148/radiol.211604] [Cited by in Crossref: 2] [Cited by in F6Publishing: 1] [Article Influence: 2.0] [Reference Citation Analysis]
3 Puttanawarut C, Sirirutbunkajorn N, Tawong N, Jiarpinitnun C, Khachonkham S, Pattaranutaporn P, Wongsawat Y. Radiomic and Dosiomic Features for the Prediction of Radiation Pneumonitis Across Esophageal Cancer and Lung Cancer. Front Oncol 2022;12:768152. [DOI: 10.3389/fonc.2022.768152] [Cited by in F6Publishing: 1] [Reference Citation Analysis]
4 Avanzo M, Gagliardi V, Stancanello J, Blanck O, Pirrone G, El Naqa I, Revelant A, Sartor G. Combining computed tomography and biologically effective dose in radiomics and deep learning improves prediction of tumor response to robotic lung stereotactic body radiation therapy. Med Phys 2021;48:6257-69. [PMID: 34415574 DOI: 10.1002/mp.15178] [Cited by in F6Publishing: 7] [Reference Citation Analysis]
5 Placidi L, Gioscio E, Garibaldi C, Rancati T, Fanizzi A, Maestri D, Massafra R, Menghi E, Mirandola A, Reggiori G, Sghedoni R, Tamborra P, Comi S, Lenkowicz J, Boldrini L, Avanzo M. A Multicentre Evaluation of Dosiomics Features Reproducibility, Stability and Sensitivity. Cancers (Basel) 2021;13:3835. [PMID: 34359737 DOI: 10.3390/cancers13153835] [Cited by in F6Publishing: 5] [Reference Citation Analysis]
6 Yan M, Wang W. A radiomics model of predicting tumor volume change of patients with stage III non-small cell lung cancer after radiotherapy. Sci Prog 2021;104:36850421997295. [PMID: 33687294 DOI: 10.1177/0036850421997295] [Cited by in F6Publishing: 1] [Reference Citation Analysis]
7 Avanzo M, Porzio M, Lorenzon L, Milan L, Sghedoni R, Russo G, Massafra R, Fanizzi A, Barucci A, Ardu V, Branchini M, Giannelli M, Gallio E, Cilla S, Tangaro S, Lombardi A, Pirrone G, De Martin E, Giuliano A, Belmonte G, Russo S, Rampado O, Mettivier G. Artificial intelligence applications in medical imaging: A review of the medical physics research in Italy. Physica Medica 2021;83:221-41. [DOI: 10.1016/j.ejmp.2021.04.010] [Cited by in Crossref: 3] [Cited by in F6Publishing: 17] [Article Influence: 3.0] [Reference Citation Analysis]
8 Zheng R, Shi C, Wang C, Shi N, Qiu T, Chen W, Shi Y, Wang H. Imaging-Based Staging of Hepatic Fibrosis in Patients with Hepatitis B: A Dynamic Radiomics Model Based on Gd-EOB-DTPA-Enhanced MRI. Biomolecules 2021;11:307. [PMID: 33670596 DOI: 10.3390/biom11020307] [Cited by in Crossref: 1] [Cited by in F6Publishing: 1] [Article Influence: 1.0] [Reference Citation Analysis]
9 Avanzo M, Trianni A, Botta F, Talamonti C, Stasi M, Iori M. Artificial Intelligence and the Medical Physicist: Welcome to the Machine. Applied Sciences 2021;11:1691. [DOI: 10.3390/app11041691] [Cited by in Crossref: 8] [Cited by in F6Publishing: 11] [Article Influence: 8.0] [Reference Citation Analysis]