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Cited by in F6Publishing
For: Weisberg EM, Chu LC, Park S, Yuille AL, Kinzler KW, Vogelstein B, Fishman EK. Deep lessons learned: Radiology, oncology, pathology, and computer science experts unite around artificial intelligence to strive for earlier pancreatic cancer diagnosis. Diagn Interv Imaging. 2020;101:111-115. [PMID: 31629672 DOI: 10.1016/j.diii.2019.09.002] [Cited by in Crossref: 14] [Cited by in F6Publishing: 11] [Article Influence: 7.0] [Reference Citation Analysis]
Number Citing Articles
1 Lin H, Xue X, Wang X, Dang S, Gu M. Application of artificial intelligence for the diagnosis, treatment, and prognosis of pancreatic cancer. AIG 2020;1:19-29. [DOI: 10.35712/aig.v1.i1.19] [Cited by in Crossref: 1] [Cited by in F6Publishing: 1] [Article Influence: 1.0] [Reference Citation Analysis]
2 Pellat A, Cottereau AS, Palmieri LJ, Soyer P, Marchese U, Brezault C, Coriat R. Digestive Well-Differentiated Grade 3 Neuroendocrine Tumors: Current Management and Future Directions. Cancers (Basel) 2021;13:2448. [PMID: 34070035 DOI: 10.3390/cancers13102448] [Reference Citation Analysis]
3 Hamamoto R, Suvarna K, Yamada M, Kobayashi K, Shinkai N, Miyake M, Takahashi M, Jinnai S, Shimoyama R, Sakai A, Takasawa K, Bolatkan A, Shozu K, Dozen A, Machino H, Takahashi S, Asada K, Komatsu M, Sese J, Kaneko S. Application of Artificial Intelligence Technology in Oncology: Towards the Establishment of Precision Medicine. Cancers (Basel). 2020;12. [PMID: 33256107 DOI: 10.3390/cancers12123532] [Cited by in Crossref: 19] [Cited by in F6Publishing: 17] [Article Influence: 19.0] [Reference Citation Analysis]
4 Courot A, Cabrera DLF, Gogin N, Gaillandre L, Rico G, Zhang-Yin J, Elhaik M, Bidault F, Bousaid I, Lassau N. Automatic cervical lymphadenopathy segmentation from CT data using deep learning. Diagn Interv Imaging 2021:S2211-5684(21)00111-X. [PMID: 34023232 DOI: 10.1016/j.diii.2021.04.009] [Cited by in Crossref: 1] [Article Influence: 1.0] [Reference Citation Analysis]
5 Barat M, Hoeffel C, Aissaoui M, Dohan A, Oudjit A, Dautry R, Paisant A, Malgras B, Cottereau AS, Soyer P. Focal splenic lesions: Imaging spectrum of diseases on CT, MRI and PET/CT. Diagn Interv Imaging 2021;102:501-13. [PMID: 33965354 DOI: 10.1016/j.diii.2021.03.006] [Reference Citation Analysis]
6 Yuan HX, Yu QH, Zhang YQ, Yu Q, Zhang Q, Wang WP. Ultrasound Radiomics Effective for Preoperative Identification of True and Pseudo Gallbladder Polyps Based on Spatial and Morphological Features. Front Oncol 2020;10:1719. [PMID: 33042816 DOI: 10.3389/fonc.2020.01719] [Cited by in Crossref: 2] [Cited by in F6Publishing: 1] [Article Influence: 2.0] [Reference Citation Analysis]
7 Bartoli M, Barat M, Dohan A, Gaujoux S, Coriat R, Hoeffel C, Cassinotto C, Chassagnon G, Soyer P. CT and MRI of pancreatic tumors: an update in the era of radiomics. Jpn J Radiol 2020;38:1111-24. [PMID: 33085029 DOI: 10.1007/s11604-020-01057-6] [Cited by in Crossref: 11] [Cited by in F6Publishing: 9] [Article Influence: 11.0] [Reference Citation Analysis]
8 Hain E, Sindayigaya R, Fawaz J, Gharios J, Bouteloup G, Soyer P, Bertherat J, Prat F, Terris B, Coriat R, Gaujoux S. Surgical management of pancreatic neuroendocrine tumors: an introduction. Expert Rev Anticancer Ther 2019;19:1089-100. [PMID: 31825691 DOI: 10.1080/14737140.2019.1703677] [Cited by in Crossref: 4] [Cited by in F6Publishing: 5] [Article Influence: 2.0] [Reference Citation Analysis]
9 Barat M, Chassagnon G, Dohan A, Gaujoux S, Coriat R, Hoeffel C, Cassinotto C, Soyer P. Artificial intelligence: a critical review of current applications in pancreatic imaging. Jpn J Radiol 2021;39:514-23. [PMID: 33550513 DOI: 10.1007/s11604-021-01098-5] [Reference Citation Analysis]
10 Parwani AV, Amin MB. Convergence of Digital Pathology and Artificial Intelligence Tools in Anatomic Pathology Practice: Current Landscape and Future Directions. Adv Anat Pathol 2020;27:221-6. [PMID: 32541593 DOI: 10.1097/PAP.0000000000000271] [Cited by in Crossref: 3] [Cited by in F6Publishing: 2] [Article Influence: 3.0] [Reference Citation Analysis]
11 Bajema IM. Machine learning in medicine: Medical droids, tricorders, and a computer named Hal 9000. Nephrol Ther 2021;17S:S51-3. [PMID: 33910698 DOI: 10.1016/j.nephro.2020.03.002] [Reference Citation Analysis]