BPG is committed to discovery and dissemination of knowledge
Cited by in F6Publishing
For: 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: 2] [Article Influence: 3.0] [Reference Citation Analysis]
Number Citing Articles
1 Mireștean CC, Volovăț C, Iancu RI, Iancu DPT. Radiomics in Triple Negative Breast Cancer: New Horizons in an Aggressive Subtype of the Disease. J Clin Med 2022;11:616. [PMID: 35160069 DOI: 10.3390/jcm11030616] [Cited by in Crossref: 1] [Article Influence: 1.0] [Reference Citation Analysis]
2 Retico A, Avanzo M, Boccali T, Bonacorsi D, Botta F, Cuttone G, Martelli B, Salomoni D, Spiga D, Trianni A, Stasi M, Iori M, Talamonti C. Enhancing the impact of Artificial Intelligence in Medicine: A joint AIFM-INFN Italian initiative for a dedicated cloud-based computing infrastructure. Phys Med 2021;91:140-50. [PMID: 34801873 DOI: 10.1016/j.ejmp.2021.10.005] [Reference Citation Analysis]
3 Bacha S, Ben Abdellafou K, Aljuhani A, Taouali O, Liouane N. Early detection of digital mammogram using kernel extreme learning machine. Concurrency and Computation 2022;34. [DOI: 10.1002/cpe.6971] [Reference Citation Analysis]
4 Chen J, Bermejo I, Dekker A, Wee L. Generative models improve radiomics performance in different tasks and different datasets: An experimental study. Phys Med 2022;98:11-7. [PMID: 35468494 DOI: 10.1016/j.ejmp.2022.04.008] [Reference Citation Analysis]
5 Amoroso N, Pomarico D, Fanizzi A, Didonna V, Giotta F, La Forgia D, Latorre A, Monaco A, Pantaleo E, Petruzzellis N, Tamborra P, Zito A, Lorusso V, Bellotti R, Massafra R. A Roadmap towards Breast Cancer Therapies Supported by Explainable Artificial Intelligence. Applied Sciences 2021;11:4881. [DOI: 10.3390/app11114881] [Cited by in Crossref: 4] [Cited by in F6Publishing: 2] [Article Influence: 4.0] [Reference Citation Analysis]
6 Bacha S, Taouali O. A novel machine learning approach for breast cancer diagnosis. Measurement 2022;187:110233. [DOI: 10.1016/j.measurement.2021.110233] [Cited by in Crossref: 1] [Article Influence: 1.0] [Reference Citation Analysis]
7 Liu M, He Y, Wu M, Zeng C. Breast Histopathological Image Classification Method Based on Autoencoder and Siamese Framework. Information 2022;13:107. [DOI: 10.3390/info13030107] [Reference Citation Analysis]
8 Zanca F, Avanzo M, Colgan N, Crijns W, Guidi G, Hernandez-Giron I, Kagadis GC, Diaz O, Zaidi H, Russo P, Toma-Dasu I, Kortesniemi M. Focus issue: Artificial intelligence in medical physics. Phys Med 2021;83:287-91. [PMID: 34004585 DOI: 10.1016/j.ejmp.2021.05.008] [Reference Citation Analysis]
9 Ubaldi L, Valenti V, Borgese RF, Collura G, Fantacci ME, Ferrera G, Iacoviello G, Abbate BF, Laruina F, Tripoli A, Retico A, Marrale M. Strategies to develop radiomics and machine learning models for lung cancer stage and histology prediction using small data samples. Phys Med 2021;90:13-22. [PMID: 34521016 DOI: 10.1016/j.ejmp.2021.08.015] [Reference Citation Analysis]