Radiomics Model for Predicting TP53 Status Using CT and Machine Learning Approach in Laryngeal Squamous Cell Carcinoma

A PET/CT nomogram incorporating SUVmax and CT radiomics for preoperative nodal staging in non-small cell lung cancer

(2021) Yunming Xie et al.   EUROPEAN RADIOLOGY

Development and validation of a MRI-based radiomics signature for prediction of KRAS mutation in rectal cancer

(2020) Yanfen Cui et al.   EUROPEAN RADIOLOGY

Radiogenomics in Clear Cell Renal Cell Carcinoma: Machine Learning–Based High-Dimensional Quantitative CT Texture Analysis in Predicting PBRM1 Mutation Status

(2019) Burak Kocak et al.   AMERICAN JOURNAL OF ROENTGENOLOGY

Identifying EGFR mutations in lung adenocarcinoma by noninvasive imaging using radiomics features and random forest modeling

(2019) Tian-Ying Jia et al.   EUROPEAN RADIOLOGY

Aberrant methylation-mediated downregulation of lncRNA SSTR5-AS1 promotes progression and metastasis of laryngeal squamous cell carcinoma

(2019) Baoshan Wang et al.   Epigenetics & Chromatin

Development and validation of radiomic signatures of head and neck squamous cell carcinoma molecular features and subtypes

(2019) Chao Huang et al.   EBioMedicine

Decoding tumor mutation burden and driver mutations in early stage lung adenocarcinoma using CT‐based radiomics signature

(2019) Xiaoxiao Wang et al.   Thoracic Cancer

Developing an individualized risk calculator for psychopathology among young people victimized during childhood: A population-representative cohort study

(2019) Alan J. Meehan et al.   JOURNAL OF AFFECTIVE DISORDERS

Radiomics analysis of pulmonary nodules in low-dose CT for early detection of lung cancer

(2018) Wookjin Choi et al.   MEDICAL PHYSICS

TP53 mutations and number of alterations correlate with maximum standardized uptake value (SUVmax) determined by positron emission tomography/computed tomography (PET/CT) [18F] fluorodeoxyglucose (18F-FDG PET)

(2018) Geraldine H. Chang et al.   Oncotarget

MRI features predict p53 status in lower-grade gliomas via a machine-learning approach

(2018) Yiming Li et al.   NeuroImage-Clinical

CDR1as is overexpressed in laryngeal squamous cell carcinoma to promote the tumour’s progression via miR-7 signals

(2018) Jianzhong Zhang et al.   CELL PROLIFERATION

Deep Learning and Radiomics predict complete response after neo-adjuvant chemoradiation for locally advanced rectal cancer

(2018) Jean-Emmanuel Bibault et al.   Scientific Reports

Comparison of a radiomic biomarker with volumetric analysis for decoding tumour phenotypes of lung adenocarcinoma with different disease-specific survival

(2017) Mei Yuan et al.   EUROPEAN RADIOLOGY

Predictive and prognostic value of CT based radiomics signature in locally advanced head and neck cancers patients treated with concurrent chemoradiotherapy or bioradiotherapy and its added value to Human Papillomavirus status

(2017) Dan Ou et al.   ORAL ONCOLOGY

Development of a novel score for the prediction of hospital mortality in patients with severe sepsis: the use of electronic healthcare records with LASSO regression

(2017) Zhongheng Zhang et al.   Oncotarget

CT-based radiomics signature: a potential biomarker for preoperative prediction of early recurrence in hepatocellular carcinoma

(2017) Ying Zhou et al.   Abdominal Radiology

An update on larynx cancer

(2016) Conor E. Steuer et al.   CA-A CANCER JOURNAL FOR CLINICIANS

TP53Mutations in Head and Neck Squamous Cell Carcinoma and Their Impact on Disease Progression and Treatment Response

(2016) Ge Zhou et al.   JOURNAL OF CELLULAR BIOCHEMISTRY

Radiogenomics to characterize regional genetic heterogeneity in glioblastoma

(2016) Leland S. Hu et al.   NEURO-ONCOLOGY

The degree of intratumor mutational heterogeneity varies by primary tumor sub-site

(2016) Levi G. Ledgerwood et al.   Oncotarget

Decoding tumour phenotype by noninvasive imaging using a quantitative radiomics approach

(2014) Hugo J. W. L. Aerts et al.   Nature Communications

Radiomics: Extracting more information from medical images using advanced feature analysis

(2012) Philippe Lambin et al.   EUROPEAN JOURNAL OF CANCER

Specific TP53 mutations predict aggressive phenotype in head and neck squamous cell carcinoma: a retrospective archival study

(2011) Jenni K Peltonen et al.   Head and Neck Optical Diagnostics Society