Results 31 to 40 of about 73,359 (292)

Predicting Treatment Response to Neoadjuvant Chemoradiotherapy in Rectal Mucinous Adenocarcinoma Using an MRI-Based Radiomics Nomogram

Frontiers in Oncology, 2021
ObjectiveTo build and validate an MRI-based radiomics nomogram to predict the therapeutic response to neoadjuvant chemoradiotherapy (nCRT) in rectal mucinous adenocarcinoma (RMAC).MethodsTotally, 92 individuals with pathologically confirmed RMAC ...
Zhihui Li, Shuai Li, Shuqin Zang, Xiaolu Ma, Fangying Chen, Yuwei Xia, Liuping Chen, Fu Shen, Yong Lu, Jianping Lu   +9 more
doaj   +1 more source

Radiomics Analysis for Predicting Epilepsy in Patients With Unruptured Brain Arteriovenous Malformations

Frontiers in Neurology, 2021
Objectives: To investigate the association between radiomics features and epilepsy in patients with unruptured brain arteriovenous malformations (bAVMs) and to develop a prediction model based on radiomics features and clinical characteristics for bAVM ...
Shaozhi Zhao, Shaozhi Zhao, Qi Zhao, Yuming Jiao, Yuming Jiao, Hao Li, Hao Li, Jiancong Weng, Jiancong Weng, Ran Huo, Ran Huo, Jie Wang, Jie Wang, Hongyuan Xu, Hongyuan Xu, Junze Zhang, Junze Zhang, Yan Li, Zhenzhou Wu, Shuo Wang, Shuo Wang, Yong Cao, Yong Cao, Jizong Zhao, Jizong Zhao   +24 more
doaj   +1 more source

Moddicom: a Complete and Easily Accessible Library for Prognostic Evaluations Relying on Image Features [PDF]

, 2015
Decision Support Systems (DSSs) are increasingly exploited in the area of prognostic evaluations. For predicting the effect of therapies on patients, the trend is now to use image features, i.e.
Alitto, Anna Rita, Autorino, Rosa, Boldrini, Luca, Damiani, Andrea, Dinapoli, Nicola, Gatta, Roberto, Valentini, Vincenzo, Vallati, Mauro   +7 more
core   +1 more source

Uncontrolled Confounders May Lead to False or Overvalued Radiomics Signature: A Proof of Concept Using Survival Analysis in a Multicenter Cohort of Kidney Cancer

Frontiers in Oncology, 2021
PurposeWe aimed to explore potential confounders of prognostic radiomics signature predicting survival outcomes in clear cell renal cell carcinoma (ccRCC) patients and demonstrate how to control for them.Materials and MethodsPreoperative contrast ...
Lin Lu, Firas S. Ahmed, Oguz Akin, Lyndon Luk, Xiaotao Guo, Hao Yang, Jin Yoon, A. Aari Hakimi, Lawrence H. Schwartz, Binsheng Zhao   +9 more
doaj   +1 more source

Quo vadis Radiomics? Bibliometric analysis of 10-year Radiomics journey

European Radiology, 2023
Abstract Objectives Radiomics is the high-throughput extraction of mineable and—possibly—reproducible quantitative imaging features from medical imaging. The aim of this work is to perform an unbiased bibliometric analysis on Radiomics 10 years after the first work became available, to highlight its status, pitfalls, and
Volpe S., Mastroleo F., Krengli M., Jereczek-Fossa B. A.   +3 more
openaire   +2 more sources

18F-FDG PET/CT-based radiomics nomogram could predict bone marrow involvement in pediatric neuroblastoma

Insights into Imaging, 2022
Objective To develop and validate an 18F-fluorodeoxyglucose (FDG) positron emission tomography/computed tomography (PET/CT)-based radiomics nomogram for non-invasively prediction of bone marrow involvement (BMI) in pediatric neuroblastoma.
Lijuan Feng, Xu Yang, Xia Lu, Ying Kan, Chao Wang, Dehui Sun, Hui Zhang, Wei Wang, Jigang Yang   +8 more
doaj   +1 more source

The predictive value of radiomics-based machine learning for peritoneal metastasis in gastric cancer patients: a systematic review and meta-analysis

Frontiers in Oncology, 2023
BackgroundFor patients with gastric cancer (GC), effective preoperative identification of peritoneal metastasis (PM) remains a severe challenge in clinical practice. Regrettably, effective early identification tools are still lacking up to now.
Fan Zhang, Guoxue Wu, Nan Chen, Ruyue Li
doaj   +1 more source

Radiomics in Spine Surgery

International Journal of Spine Surgery, 2023
Radiomics is an emerging approach to analyze clinical images with the purpose of revealing quantitative features that are unvisible to the naked eye. Radiomic features can be further combined with clinical data and genomic information to formulate prediction models using machine learning algorithms or manual statistical analysis.
Daniel, Alsoof, Christopher L, McDonald, Wesley M, Durand, Bassel G, Diebo, Eren O, Kuris, Alan H, Daniels   +5 more
openaire   +2 more sources

Radiomics-Based Outcome Prediction for Pancreatic Cancer Following Stereotactic Body Radiotherapy [PDF]

, 2020
(1) Background: Radiomics use high-throughput mining of medical imaging data to extract unique information and predict tumor behavior. Currently available clinical prediction models poorly predict treatment outcomes in pancreatic adenocarcinoma ...
Baine, Michael, Bavitz, Kyle, Du, Qian, Hollingsworth, Michael, Kamal, Ahsan, Liang, Xiaoying, Lin, Chi, McAlister, Josiah, Parr, Elsa, Rux, Gerard, Zhang, Chi, Zheng, Dandan   +11 more
core   +1 more source

Discovery Radiomics via Deep Multi-Column Radiomic Sequencers for Skin Cancer Detection [PDF]

, 2017
While skin cancer is the most diagnosed form of cancer in men and women, with more cases diagnosed each year than all other cancers combined, sufficiently early diagnosis results in very good prognosis and as such makes early detection crucial.
Shafiee, Mohammad Javad, Wong, Alexander
core   +3 more sources