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Refinado por: Base de dados/Biblioteca: CINAHL with Full Text remover Base de dados/Biblioteca: SpringerLink remover Ovid SocietyJournals and Single Titles remover
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1
Quality of science and reporting of radiomics in oncologic studies: room for improvement according to radiomics quality score and TRIPOD statement
Quality of science and reporting of radiomics in oncologic studies: room for improvement according to radiomics quality score and TRIPOD statement
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Quality of science and reporting of radiomics in oncologic studies: room for improvement according to radiomics quality score and TRIPOD statement

Park, Ji Eun ; Kim, Donghyun ; Kim, Ho Sung ; Park, Seo Young ; Kim, Jung Youn ; Cho, Se Jin ; Shin, Jae Ho ; Kim, Jeong Hoon

European radiology, 2020-01, Vol.30 (1), p.523-536 [Periódico revisado por pares]

Berlin/Heidelberg: Springer Berlin Heidelberg

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2
Radiomics of computed tomography and magnetic resonance imaging in renal cell carcinoma—a systematic review and meta-analysis
Radiomics of computed tomography and magnetic resonance imaging in renal cell carcinoma—a systematic review and meta-analysis
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Radiomics of computed tomography and magnetic resonance imaging in renal cell carcinoma—a systematic review and meta-analysis

Ursprung, Stephan ; Beer, Lucian ; Bruining, Annemarie ; Woitek, Ramona ; Stewart, Grant D ; Gallagher, Ferdia A ; Sala, Evis

European radiology, 2020-06, Vol.30 (6), p.3558-3566 [Periódico revisado por pares]

Berlin/Heidelberg: Springer Berlin Heidelberg

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3
Machine learning for the identification of clinically significant prostate cancer on MRI: a meta-analysis
Machine learning for the identification of clinically significant prostate cancer on MRI: a meta-analysis
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Machine learning for the identification of clinically significant prostate cancer on MRI: a meta-analysis

Cuocolo, Renato ; Cipullo, Maria Brunella ; Stanzione, Arnaldo ; Romeo, Valeria ; Green, Roberta ; Cantoni, Valeria ; Ponsiglione, Andrea ; Ugga, Lorenzo ; Imbriaco, Massimo

European radiology, 2020-12, Vol.30 (12), p.6877-6887 [Periódico revisado por pares]

Berlin/Heidelberg: Springer Berlin Heidelberg

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4
A systematic review of radiomics in osteosarcoma: utilizing radiomics quality score as a tool promoting clinical translation
A systematic review of radiomics in osteosarcoma: utilizing radiomics quality score as a tool promoting clinical translation
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A systematic review of radiomics in osteosarcoma: utilizing radiomics quality score as a tool promoting clinical translation

Zhong, Jingyu ; Hu, Yangfan ; Si, Liping ; Jia, Geng ; Xing, Yue ; Zhang, Huan ; Yao, Weiwu

European radiology, 2021-03, Vol.31 (3), p.1526-1535 [Periódico revisado por pares]

Berlin/Heidelberg: Springer Berlin Heidelberg

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5
How to read and review papers on machine learning and artificial intelligence in radiology: a survival guide to key methodological concepts
How to read and review papers on machine learning and artificial intelligence in radiology: a survival guide to key methodological concepts
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How to read and review papers on machine learning and artificial intelligence in radiology: a survival guide to key methodological concepts

Kocak, Burak ; Kus, Ece Ates ; Kilickesmez, Ozgur

European radiology, 2021-04, Vol.31 (4), p.1819-1830 [Periódico revisado por pares]

Berlin/Heidelberg: Springer Berlin Heidelberg

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6
Radiomics nomogram for predicting the malignant potential of gastrointestinal stromal tumours preoperatively
Radiomics nomogram for predicting the malignant potential of gastrointestinal stromal tumours preoperatively
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Radiomics nomogram for predicting the malignant potential of gastrointestinal stromal tumours preoperatively

Chen, Tao ; Ning, Zhenyuan ; Xu, Lili ; Feng, Xingyu ; Han, Shuai ; Roth, Holger R. ; Xiong, Wei ; Zhao, Xixi ; Hu, Yanfeng ; Liu, Hao ; Yu, Jiang ; Zhang, Yu ; Li, Yong ; Xu, Yikai ; Mori, Kensaku ; Li, Guoxin

European radiology, 2019-03, Vol.29 (3), p.1074-1082 [Periódico revisado por pares]

Berlin/Heidelberg: Springer Berlin Heidelberg

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7
Taming the chaos?! Using eXplainable Artificial Intelligence (XAI) to tackle the complexity in mental health research
Taming the chaos?! Using eXplainable Artificial Intelligence (XAI) to tackle the complexity in mental health research
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Taming the chaos?! Using eXplainable Artificial Intelligence (XAI) to tackle the complexity in mental health research

Roessner, Veit ; Rothe, Josefine ; Kohls, Gregor ; Schomerus, Georg ; Ehrlich, Stefan ; Beste, Christian

European child & adolescent psychiatry, 2021-08, Vol.30 (8), p.1143-1146 [Periódico revisado por pares]

Berlin/Heidelberg: Springer Berlin Heidelberg

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8
Diagnostic accuracy and potential covariates for machine learning to identify IDH mutations in glioma patients: evidence from a meta-analysis
Diagnostic accuracy and potential covariates for machine learning to identify IDH mutations in glioma patients: evidence from a meta-analysis
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Diagnostic accuracy and potential covariates for machine learning to identify IDH mutations in glioma patients: evidence from a meta-analysis

Zhao, Jing ; Huang, Yingqian ; Song, Yukun ; Xie, Dingxiang ; Hu, Manshi ; Qiu, Haishan ; Chu, Jianping

European radiology, 2020-08, Vol.30 (8), p.4664-4674 [Periódico revisado por pares]

Berlin/Heidelberg: Springer Berlin Heidelberg

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9
Prognostic value of anthropometric measures extracted from whole-body CT using deep learning in patients with non-small-cell lung cancer
Prognostic value of anthropometric measures extracted from whole-body CT using deep learning in patients with non-small-cell lung cancer
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Prognostic value of anthropometric measures extracted from whole-body CT using deep learning in patients with non-small-cell lung cancer

Blanc-Durand, Paul ; Campedel, Luca ; Mule, Sébastien ; Jegou, Simon ; Luciani, Alain ; Pigneur, Frédéric ; Itti, Emmanuel

European radiology, 2020-06, Vol.30 (6), p.3528-3537 [Periódico revisado por pares]

Berlin/Heidelberg: Springer Berlin Heidelberg

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10
Survival-relevant high-risk subregion identification for glioblastoma patients: the MRI-based multiple instance learning approach
Survival-relevant high-risk subregion identification for glioblastoma patients: the MRI-based multiple instance learning approach
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Survival-relevant high-risk subregion identification for glioblastoma patients: the MRI-based multiple instance learning approach

Zhang, Xi ; Lu, Di ; Gao, Peng ; Tian, Qiang ; Lu, Hongbing ; Xu, Xiaopan ; He, Xiaowei ; Liu, Yang

European radiology, 2020-10, Vol.30 (10), p.5602-5610 [Periódico revisado por pares]

Berlin/Heidelberg: Springer Berlin Heidelberg

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