A citation-based method for searching scientific literature

Tianwen Xie, Zhe Wang, Qiufeng Zhao, Qianming Bai, Xiaoyan Zhou, Yajia Gu, Weijun Peng, He Wang. Front Oncol 2019
Times Cited: 37







List of co-cited articles
179 articles co-cited >1



Times Cited
  Times     Co-cited
Similarity


Radiomics: Images Are More than Pictures, They Are Data.
Robert J Gillies, Paul E Kinahan, Hedvig Hricak. Radiology 2016
40

Radiomics: the bridge between medical imaging and personalized medicine.
Philippe Lambin, Ralph T H Leijenaar, Timo M Deist, Jurgen Peerlings, Evelyn E C de Jong, Janita van Timmeren, Sebastian Sanduleanu, Ruben T H M Larue, Aniek J G Even, Arthur Jochems,[...]. Nat Rev Clin Oncol 2017
27

Radiomics of Multiparametric MRI for Pretreatment Prediction of Pathologic Complete Response to Neoadjuvant Chemotherapy in Breast Cancer: A Multicenter Study.
Zhenyu Liu, Zhuolin Li, Jinrong Qu, Renzhi Zhang, Xuezhi Zhou, Longfei Li, Kai Sun, Zhenchao Tang, Hui Jiang, Hailiang Li,[...]. Clin Cancer Res 2019
167
21

MR Imaging Radiomics Signatures for Predicting the Risk of Breast Cancer Recurrence as Given by Research Versions of MammaPrint, Oncotype DX, and PAM50 Gene Assays.
Hui Li, Yitan Zhu, Elizabeth S Burnside, Karen Drukker, Katherine A Hoadley, Cheng Fan, Suzanne D Conzen, Gary J Whitman, Elizabeth J Sutton, Jose M Net,[...]. Radiology 2016
281
21

Preoperative prediction of sentinel lymph node metastasis in breast cancer based on radiomics of T2-weighted fat-suppression and diffusion-weighted MRI.
Yuhao Dong, Qianjin Feng, Wei Yang, Zixiao Lu, Chunyan Deng, Lu Zhang, Zhouyang Lian, Jing Liu, Xiaoning Luo, Shufang Pei,[...]. Eur Radiol 2018
137
21

Intratumoral and peritumoral radiomics for the pretreatment prediction of pathological complete response to neoadjuvant chemotherapy based on breast DCE-MRI.
Nathaniel M Braman, Maryam Etesami, Prateek Prasanna, Christina Dubchuk, Hannah Gilmore, Pallavi Tiwari, Donna Plecha, Anant Madabhushi. Breast Cancer Res 2017
291
21

Quantitative MRI radiomics in the prediction of molecular classifications of breast cancer subtypes in the TCGA/TCIA data set.
Hui Li, Yitan Zhu, Elizabeth S Burnside, Erich Huang, Karen Drukker, Katherine A Hoadley, Cheng Fan, Suzanne D Conzen, Margarita Zuley, Jose M Net,[...]. NPJ Breast Cancer 2016
195
18

Decoding tumour phenotype by noninvasive imaging using a quantitative radiomics approach.
Hugo J W L Aerts, Emmanuel Rios Velazquez, Ralph T H Leijenaar, Chintan Parmar, Patrick Grossmann, Sara Carvalho, Johan Bussink, René Monshouwer, Benjamin Haibe-Kains, Derek Rietveld,[...]. Nat Commun 2014
18

Radiomics Signature on Magnetic Resonance Imaging: Association with Disease-Free Survival in Patients with Invasive Breast Cancer.
Hyunjin Park, Yaeji Lim, Eun Sook Ko, Hwan-Ho Cho, Jeong Eon Lee, Boo-Kyung Han, Eun Young Ko, Ji Soo Choi, Ko Woon Park. Clin Cancer Res 2018
121
18

Breast Cancer Molecular Subtype Prediction by Mammographic Radiomic Features.
Wenjuan Ma, Yumei Zhao, Yu Ji, Xinpeng Guo, Xiqi Jian, Peifang Liu, Shandong Wu. Acad Radiol 2019
49
18

Radiomic analysis reveals DCE-MRI features for prediction of molecular subtypes of breast cancer.
Ming Fan, Hui Li, Shijian Wang, Bin Zheng, Juan Zhang, Lihua Li. PLoS One 2017
78
18

Differentiation of triple-negative breast cancer from other subtypes through whole-tumor histogram analysis on multiparametric MR imaging.
Tianwen Xie, Qiufeng Zhao, Caixia Fu, Qianming Bai, Xiaoyan Zhou, Lihua Li, Robert Grimm, Li Liu, Yajia Gu, Weijun Peng. Eur Radiol 2019
46
18


Radiomic Signatures Derived from Diffusion-Weighted Imaging for the Assessment of Breast Cancer Receptor Status and Molecular Subtypes.
Doris Leithner, Blanca Bernard-Davila, Danny F Martinez, Joao V Horvat, Maxine S Jochelson, Maria Adele Marino, Daly Avendano, R Elena Ochoa-Albiztegui, Elizabeth J Sutton, Elizabeth A Morris,[...]. Mol Imaging Biol 2020
38
16

Computational Radiomics System to Decode the Radiographic Phenotype.
Joost J M van Griethuysen, Andriy Fedorov, Chintan Parmar, Ahmed Hosny, Nicole Aucoin, Vivek Narayan, Regina G H Beets-Tan, Jean-Christophe Fillion-Robin, Steve Pieper, Hugo J W L Aerts. Cancer Res 2017
16

The Applications of Radiomics in Precision Diagnosis and Treatment of Oncology: Opportunities and Challenges.
Zhenyu Liu, Shuo Wang, Di Dong, Jingwei Wei, Cheng Fang, Xuezhi Zhou, Kai Sun, Longfei Li, Bo Li, Meiyun Wang,[...]. Theranostics 2019
294
16


Changes in primary breast cancer heterogeneity may augment midtreatment MR imaging assessment of response to neoadjuvant chemotherapy.
Jyoti Parikh, Mariyah Selmi, Geoff Charles-Edwards, Jennifer Glendenning, Balaji Ganeshan, Hema Verma, Janine Mansi, Mark Harries, Andrew Tutt, Vicky Goh. Radiology 2014
87
13

Prediction of malignancy by a radiomic signature from contrast agent-free diffusion MRI in suspicious breast lesions found on screening mammography.
Sebastian Bickelhaupt, Daniel Paech, Philipp Kickingereder, Franziska Steudle, Wolfgang Lederer, Heidi Daniel, Michael Götz, Nils Gählert, Diana Tichy, Manuel Wiesenfarth,[...]. J Magn Reson Imaging 2017
82
13

Radiomics Based on Adapted Diffusion Kurtosis Imaging Helps to Clarify Most Mammographic Findings Suspicious for Cancer.
Sebastian Bickelhaupt, Paul Ferdinand Jaeger, Frederik Bernd Laun, Wolfgang Lederer, Heidi Daniel, Tristan Anselm Kuder, Lorenz Wuesthof, Daniel Paech, David Bonekamp, Alexander Radbruch,[...]. Radiology 2018
61
13

Impact of Machine Learning With Multiparametric Magnetic Resonance Imaging of the Breast for Early Prediction of Response to Neoadjuvant Chemotherapy and Survival Outcomes in Breast Cancer Patients.
Amirhessam Tahmassebi, Georg J Wengert, Thomas H Helbich, Zsuzsanna Bago-Horvath, Sousan Alaei, Rupert Bartsch, Peter Dubsky, Pascal Baltzer, Paola Clauser, Panagiotis Kapetas,[...]. Invest Radiol 2019
109
13

Non-Invasive Assessment of Breast Cancer Molecular Subtypes with Multiparametric Magnetic Resonance Imaging Radiomics.
Doris Leithner, Marius E Mayerhoefer, Danny F Martinez, Maxine S Jochelson, Elizabeth A Morris, Sunitha B Thakur, Katja Pinker. J Clin Med 2020
28
17

Radiomics: the process and the challenges.
Virendra Kumar, Yuhua Gu, Satrajit Basu, Anders Berglund, Steven A Eschrich, Matthew B Schabath, Kenneth Forster, Hugo J W L Aerts, Andre Dekker, David Fenstermacher,[...]. Magn Reson Imaging 2012
10

Prediction of clinical phenotypes in invasive breast carcinomas from the integration of radiomics and genomics data.
Wentian Guo, Hui Li, Yitan Zhu, Li Lan, Shengjie Yang, Karen Drukker, Elizabeth Morris, Elizabeth Burnside, Gary Whitman, Maryellen L Giger,[...]. J Med Imaging (Bellingham) 2015
95
10

Most-enhancing tumor volume by MRI radiomics predicts recurrence-free survival "early on" in neoadjuvant treatment of breast cancer.
Karen Drukker, Hui Li, Natalia Antropova, Alexandra Edwards, John Papaioannou, Maryellen L Giger. Cancer Imaging 2018
34
11

Preoperative Prediction of Axillary Lymph Node Metastasis in Breast Cancer using Radiomics Features of DCE-MRI.
Xiaoyu Cui, Nian Wang, Yue Zhao, Shuo Chen, Songbai Li, Mingjie Xu, Ruimei Chai. Sci Rep 2019
45
10

Preoperative prediction of sentinel lymph node metastasis in breast cancer by radiomic signatures from dynamic contrast-enhanced MRI.
Chunling Liu, Jie Ding, Karl Spuhler, Yi Gao, Mario Serrano Sosa, Meghan Moriarty, Shahid Hussain, Xiang He, Changhong Liang, Chuan Huang. J Magn Reson Imaging 2019
97
10

Radiomic analysis of DCE-MRI for prediction of response to neoadjuvant chemotherapy in breast cancer patients.
Ming Fan, Guolin Wu, Hu Cheng, Juan Zhang, Guoliang Shao, Lihua Li. Eur J Radiol 2017
77
10

Radiomic signatures with contrast-enhanced magnetic resonance imaging for the assessment of breast cancer receptor status and molecular subtypes: initial results.
Doris Leithner, Joao V Horvat, Maria Adele Marino, Blanca Bernard-Davila, Maxine S Jochelson, R Elena Ochoa-Albiztegui, Danny F Martinez, Elizabeth A Morris, Sunitha Thakur, Katja Pinker. Breast Cancer Res 2019
46
10

Multivariate machine learning models for prediction of pathologic response to neoadjuvant therapy in breast cancer using MRI features: a study using an independent validation set.
Elizabeth Hope Cain, Ashirbani Saha, Michael R Harowicz, Jeffrey R Marks, P Kelly Marcom, Maciej A Mazurowski. Breast Cancer Res Treat 2019
63
10

Assessment of tumor heterogeneity: an emerging imaging tool for clinical practice?
Fergus Davnall, Connie S P Yip, Gunnar Ljungqvist, Mariyah Selmi, Francesca Ng, Bal Sanghera, Balaji Ganeshan, Kenneth A Miles, Gary J Cook, Vicky Goh. Insights Imaging 2012
573
10

Identifying Triple-Negative Breast Cancer Using Background Parenchymal Enhancement Heterogeneity on Dynamic Contrast-Enhanced MRI: A Pilot Radiomics Study.
Jeff Wang, Fumi Kato, Noriko Oyama-Manabe, Ruijiang Li, Yi Cui, Khin Khin Tha, Hiroko Yamashita, Kohsuke Kudo, Hiroki Shirato. PLoS One 2015
91
10

Precision Medicine and Radiogenomics in Breast Cancer: New Approaches toward Diagnosis and Treatment.
Katja Pinker, Joanne Chin, Amy N Melsaether, Elizabeth A Morris, Linda Moy. Radiology 2018
120
10

An MRI-based Radiomics Classifier for Preoperative Prediction of Ki-67 Status in Breast Cancer.
Cuishan Liang, Zixuan Cheng, Yanqi Huang, Lan He, Xin Chen, Zelan Ma, Xiaomei Huang, Changhong Liang, Zaiyi Liu. Acad Radiol 2018
52
10

The Application of Radiomics in Breast MRI: A Review.
Dong-Man Ye, Hao-Tian Wang, Tao Yu. Technol Cancer Res Treat 2020
30
13


Applications and limitations of radiomics.
Stephen S F Yip, Hugo J W L Aerts. Phys Med Biol 2016
534
8



Race, breast cancer subtypes, and survival in the Carolina Breast Cancer Study.
Lisa A Carey, Charles M Perou, Chad A Livasy, Lynn G Dressler, David Cowan, Kathleen Conway, Gamze Karaca, Melissa A Troester, Chiu Kit Tse, Sharon Edmiston,[...]. JAMA 2006
8

Radiomics: the facts and the challenges of image analysis.
Stefania Rizzo, Francesca Botta, Sara Raimondi, Daniela Origgi, Cristiana Fanciullo, Alessio Giuseppe Morganti, Massimo Bellomi. Eur Radiol Exp 2018
387
8

Computerized image analysis for identifying triple-negative breast cancers and differentiating them from other molecular subtypes of breast cancer on dynamic contrast-enhanced MR images: a feasibility study.
Shannon C Agner, Mark A Rosen, Sarah Englander, John E Tomaszewski, Michael D Feldman, Paul Zhang, Carolyn Mies, Mitchell D Schnall, Anant Madabhushi. Radiology 2014
98
8

Preoperative Prediction of Axillary Lymph Node Metastasis in Breast Cancer Using Mammography-Based Radiomics Method.
Jingbo Yang, Tao Wang, Lifeng Yang, Yubo Wang, Hongmei Li, Xiaobo Zhou, Weiling Zhao, Junchan Ren, Xiaoyong Li, Jie Tian,[...]. Sci Rep 2019
37
8



Multiparametric MRI-based radiomics analysis for prediction of breast cancers insensitive to neoadjuvant chemotherapy.
Qianqian Xiong, Xuezhi Zhou, Zhenyu Liu, Chuqian Lei, Ciqiu Yang, Mei Yang, Liulu Zhang, Teng Zhu, Xiaosheng Zhuang, Changhong Liang,[...]. Clin Transl Oncol 2020
43
8

Radiomics: extracting more information from medical images using advanced feature analysis.
Philippe Lambin, Emmanuel Rios-Velazquez, Ralph Leijenaar, Sara Carvalho, Ruud G P M van Stiphout, Patrick Granton, Catharina M L Zegers, Robert Gillies, Ronald Boellard, André Dekker,[...]. Eur J Cancer 2012
8

An exploratory radiomics analysis on digital breast tomosynthesis in women with mammographically negative dense breasts.
Alberto Stefano Tagliafico, Francesca Valdora, Giovanna Mariscotti, Maunela Durando, Jacopo Nori, Daniele La Forgia, Ilan Rosenberg, Francesca Caumo, Nicoletta Gandolfo, Nehmat Houssami,[...]. Breast 2018
29
10

Digital Mammography in Breast Cancer: Additive Value of Radiomics of Breast Parenchyma.
Hui Li, Kayla R Mendel, Li Lan, Deepa Sheth, Maryellen L Giger. Radiology 2019
37
8

DCE-MRI Pharmacokinetic-Based Phenotyping of Invasive Ductal Carcinoma: A Radiomic Study for Prediction of Histological Outcomes.
Serena Monti, Marco Aiello, Mariarosaria Incoronato, Anna Maria Grimaldi, Michela Moscarino, Peppino Mirabelli, Umberto Ferbo, Carlo Cavaliere, Marco Salvatore. Contrast Media Mol Imaging 2018
28
10


Co-cited is the co-citation frequency, indicating how many articles cite the article together with the query article. Similarity is the co-citation as percentage of the times cited of the query article or the article in the search results, whichever is the lowest. These numbers are calculated for the last 100 citations when articles are cited more than 100 times.