Patrick Großmann
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View article: Deep learning for lung cancer prognostication: A retrospective multi-cohort radiomics study
Deep learning for lung cancer prognostication: A retrospective multi-cohort radiomics study Open
Our results provide evidence that deep learning networks may be used for mortality risk stratification based on standard-of-care CT images from NSCLC patients. This evidence motivates future research into better deciphering the clinical an…
View article: Defining the biological basis of radiomic phenotypes in lung cancer
Defining the biological basis of radiomic phenotypes in lung cancer Open
Medical imaging can visualize characteristics of human cancer noninvasively. Radiomics is an emerging field that translates these medical images into quantitative data to enable phenotypic profiling of tumors. While radiomics has been asso…
View article: Correction: Corrigendum: Recurrent hormone-binding domain truncated ESR1 amplifications in primary endometrial cancers suggest their implication in hormone independent growth
Correction: Corrigendum: Recurrent hormone-binding domain truncated ESR1 amplifications in primary endometrial cancers suggest their implication in hormone independent growth Open
Scientific Reports 6: Article number: 25521; published online: 10 May 2016; updated: 30 June 2017 This Article contains errors in the frequencies of ESR1 amplifications concerning uterine corpus endometrioid carcinoma (UCEC) in TCGA, which…
View article: Author response: Defining the biological basis of radiomic phenotypes in lung cancer
Author response: Defining the biological basis of radiomic phenotypes in lung cancer Open
Article Figures and data Abstract eLife digest Introduction Results Discussion Materials and methods Data availability References Decision letter Author response Article and author information Metrics Abstract Medical imaging can visualize…
View article: Quantitative imaging biomarkers for risk stratification of patients with recurrent glioblastoma treated with bevacizumab
Quantitative imaging biomarkers for risk stratification of patients with recurrent glioblastoma treated with bevacizumab Open
Radiomics provides prognostic value for survival and progression in patients with recurrent glioblastoma receiving bevacizumab treatment. These results could lead to the development of quantitative pretreatment biomarkers to predict benefi…
View article: Correction: Corrigendum: Defining a Radiomic Response Phenotype: A Pilot Study using targeted therapy in NSCLC
Correction: Corrigendum: Defining a Radiomic Response Phenotype: A Pilot Study using targeted therapy in NSCLC Open
Scientific Reports 6: Article number: 33860; published online: 20 September 2016; updated: 17 February 2017 The original version of this Article contained a typographical error in the spelling of the author Geoffrey R. Oxnard, which was in…
View article: Defining a Radiomic Response Phenotype: A Pilot Study using targeted therapy in NSCLC
Defining a Radiomic Response Phenotype: A Pilot Study using targeted therapy in NSCLC Open
Medical imaging plays a fundamental role in oncology and drug development, by providing a non-invasive method to visualize tumor phenotype. Radiomics can quantify this phenotype comprehensively by applying image-characterization algorithms…
View article: Correction: Corrigendum: Recurrent hormone-binding domain truncated ESR1 amplifications in primary endometrial cancers suggest their implication in hormone independent growth
Correction: Corrigendum: Recurrent hormone-binding domain truncated ESR1 amplifications in primary endometrial cancers suggest their implication in hormone independent growth Open
Scientific Reports 6: Article number: 25521; published online: 10 May 2016; updated: 24 June 2016 In the original version of this Article, there were errors in Affiliation 2 which was incorrectly given as ‘KG Jebsen Center for Precision Me…
View article: Integration of TP53, DREAM, MMB-FOXM1 and RB-E2F target gene analyses identifies cell cycle gene regulatory networks
Integration of TP53, DREAM, MMB-FOXM1 and RB-E2F target gene analyses identifies cell cycle gene regulatory networks Open
Cell cycle (CC) and TP53 regulatory networks are frequently deregulated in cancer. While numerous genome-wide studies of TP53 and CC-regulated genes have been performed, significant variation between studies has made it difficult to assess…
View article: Exploratory Study to Identify Radiomics Classifiers for Lung Cancer Histology
Exploratory Study to Identify Radiomics Classifiers for Lung Cancer Histology Open
Histological subtypes can influence the choice of a treatment/therapy for lung cancer patients. We observed that radiomic features show significant association with the lung tumor histology. Moreover, radiomics-based multivariate classifie…