Literature DB >> 28693537

Erratum to: Intratumoral and peritumoral radiomics for the pretreatment prediction of pathological complete response to neoadjuvant chemotherapy based on breast DCE-MRI.

Nathaniel M Braman1, Maryam Etesami2, Prateek Prasanna3, Christina Dubchuk2, Hannah Gilmore2, Pallavi Tiwari3, Donna Plecha2, Anant Madabhushi3.   

Abstract

Entities:  

Year:  2017        PMID： 28693537      PMCID： PMC5502485          DOI： 10.1186/s13058-017-0862-1

Source DB:  PubMed          Journal:  Breast Cancer Res        ISSN： 1465-5411            Impact factor:   6.466


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Erratum

This article [1] has been updated to correct the spelling of one of the author’s names. Donna Plecha’s name was incorrectly spelt as Pletcha when this article originally published.
  1 in total

1.  Intratumoral and peritumoral radiomics for the pretreatment prediction of pathological complete response to neoadjuvant chemotherapy based on breast DCE-MRI.

Authors:  Nathaniel M Braman; Maryam Etesami; Prateek Prasanna; Christina Dubchuk; Hannah Gilmore; Pallavi Tiwari; Donna Plecha; Anant Madabhushi
Journal:  Breast Cancer Res       Date:  2017-05-18       Impact factor: 6.466
  1 in total
  7 in total

1.  Multi-center evaluation of artificial intelligent imaging and clinical models for predicting neoadjuvant chemotherapy response in breast cancer.

Authors:  Tan Hong Qi; Ong Hiok Hian; Arjunan Muthu Kumaran; Tira J Tan; Tan Ryan Ying Cong; Ghislaine Lee Su-Xin; Elaine Hsuen Lim; Raymond Ng; Ming Chert Richard Yeo; Faye Lynette Lim Wei Tching; Zhang Zewen; Christina Yang Shi Hui; Wong Ru Xin; Su Kai Gideon Ooi; Lester Chee Hao Leong; Su Ming Tan; Madhukumar Preetha; Yirong Sim; Veronique Kiak Mien Tan; Joe Yeong; Wong Fuh Yong; Yiyu Cai; Wen Long Nei
Journal:  Breast Cancer Res Treat       Date:  2022-03-09       Impact factor: 4.872

Review 2.  A New Challenge for Radiologists: Radiomics in Breast Cancer.

Authors:  Paola Crivelli; Roberta Eufrasia Ledda; Nicola Parascandolo; Alberto Fara; Daniela Soro; Maurizio Conti
Journal:  Biomed Res Int       Date:  2018-10-08       Impact factor: 3.411

3.  Correlation Between Mammographic Radiomics Features and the Level of Tumor-Infiltrating Lymphocytes in Patients With Triple-Negative Breast Cancer.

Authors:  Hongwei Yu; Xianqi Meng; Huang Chen; Xiaowei Han; Jingfan Fan; Wenwen Gao; Lei Du; Yue Chen; Yige Wang; Xiuxiu Liu; Lu Zhang; Guolin Ma; Jian Yang
Journal:  Front Oncol       Date:  2020-04-15       Impact factor: 6.244

4.  Could Ultrasound-Based Radiomics Noninvasively Predict Axillary Lymph Node Metastasis in Breast Cancer?

Authors:  Xiaoying Qiu; Yongluo Jiang; Qiyu Zhao; Chunhong Yan; Min Huang; Tian'an Jiang
Journal:  J Ultrasound Med       Date:  2020-04-24       Impact factor: 2.153

5.  XGBoost Classifier Based on Computed Tomography Radiomics for Prediction of Tumor-Infiltrating CD8+ T-Cells in Patients With Pancreatic Ductal Adenocarcinoma.

Authors:  Jing Li; Zhang Shi; Fang Liu; Xu Fang; Kai Cao; Yinghao Meng; Hao Zhang; Jieyu Yu; Xiaochen Feng; Qi Li; Yanfang Liu; Li Wang; Hui Jiang; Jianping Lu; Chengwei Shao; Yun Bian
Journal:  Front Oncol       Date:  2021-05-19       Impact factor: 6.244

6.  Multiparametric MRI-based radiomics analysis for the prediction of breast tumor regression patterns after neoadjuvant chemotherapy.

Authors:  Xiaosheng Zhuang; Chi Chen; Zhenyu Liu; Liulu Zhang; Xuezhi Zhou; Minyi Cheng; Fei Ji; Teng Zhu; Chuqian Lei; Junsheng Zhang; Jingying Jiang; Jie Tian; Kun Wang
Journal:  Transl Oncol       Date:  2020-08-03       Impact factor: 4.243

Review 7.  Current Status and Future Perspectives of Artificial Intelligence in Magnetic Resonance Breast Imaging.

Authors:  Anke Meyer-Bäse; Lia Morra; Uwe Meyer-Bäse; Katja Pinker
Journal:  Contrast Media Mol Imaging       Date:  2020-08-28       Impact factor: 3.161
  7 in total

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