Results 111 to 120 of about 71,655 (241)

FeAture Explorer (FAE): A tool for developing and comparing radiomics models

PLoS ONE, 2020
In radiomics studies, researchers usually need to develop a supervised machine learning model to map image features onto the clinical conclusion. A classical machine learning pipeline consists of several steps, including normalization, feature selection,
Yang Song, Jing Zhang, Yu-Dong Zhang, Ying Hou, Xu Yan, Yida Wang, Min-Xiong Zhou, Yefeng Yao, Guang Yang   +8 more
semanticscholar   +1 more source

Machine learning-based CT radiomics model for predicting hospital stay in patients with pneumonia associated with SARS-CoV-2 infection: A multicenter study

medRxiv, 2020
Objectives To develop and test machine learning-based CT radiomics models for predicting hospital stay in patients with pneumonia associated with SARS-CoV-2 infection.
X. Qi, Zicheng Jiang, Qian Yu, C. Shao, Hongguang Zhang, H. Yue, B. Ma, Yuan-Cheng Wang, Chuan Liu, Xiangpan Meng, Shan Huang, Jitao Wang, Dan Xu, J. Lei, Guanghang Xie, Huihong Huang, Jie Yang, J. Ji, H. Pan, S. Zou, S. Ju   +20 more
semanticscholar   +1 more source

Novel Nomogram for Preoperative Prediction of Early Recurrence in Intrahepatic Cholangiocarcinoma

Frontiers in Oncology, 2018
Introduction: The emerging field of “radiomics” has considerable potential in disease diagnosis, pathologic grading, prognosis evaluation, and prediction of treatment response.
Wenjie Liang, Wenjie Liang, Lei Xu, Lei Xu, Pengfei Yang, Pengfei Yang, Lele Zhang, Lele Zhang, Lele Zhang, Dalong Wan, Qiang Huang, Tianye Niu, Feng Chen   +12 more
doaj   +1 more source

A Survey on Recent Advancements for AI Enabled Radiomics in Neuro-Oncology [PDF]

arXiv, 2019
Artificial intelligence (AI) enabled radiomics has evolved immensely especially in the field of oncology. Radiomics provide assistancein diagnosis of cancer, planning of treatment strategy, and predictionof survival. Radiomics in neuro-oncology has progressed significantly inthe recent past.
arxiv  

Editorial: Imaging assessment of response to immunotherapy

Frontiers in Oncology, 2023
Mariaelena Occhipinti, Andrea R. Filippi, Andrea R. Filippi, Sean Walsh, Jan P. van Meerbeeck   +4 more
doaj   +1 more source

Radiomics signature of computed tomography imaging for prediction of survival and chemotherapeutic benefits in gastric cancerResearch in context

EBioMedicine, 2018
To develop and validate a radiomics signature for the prediction of gastric cancer (GC) survival and chemotherapeutic benefits. In this multicenter retrospective analysis, we analyzed the radiomics features of portal venous-phase computed tomography in ...
Yuming Jiang, Chuanli Chen, Jingjing Xie, Wei Wang, Xuefan Zha, Wenbing Lv, Hao Chen, Yanfeng Hu, Tuanjie Li, Jiang Yu, Zhiwei Zhou, Yikai Xu, Guoxin Li   +12 more
doaj  

Multifactorial decision support systems in radiation oncology : clinical predictors and radiomics [PDF]

, 2014
Emmanuel Rios Velazquez
openalex   +1 more source

Discovery Radiomics for Multi-Parametric MRI Prostate Cancer Detection [PDF]

arXiv, 2015
Prostate cancer is the most diagnosed form of cancer in Canadian men, and is the third leading cause of cancer death. Despite these statistics, prognosis is relatively good with a sufficiently early diagnosis, making fast and reliable prostate cancer detection crucial. As imaging-based prostate cancer screening, such as magnetic resonance imaging (MRI),
arxiv  

Correction: Corrigendum: Decoding tumour phenotype by noninvasive imaging using a quantitative radiomics approach [PDF]

, 2014
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, D. Rietveld, Frank Hoebers, Michelle M. Rietbergen, C. René Leemans, André Dekker, John Quackenbush, Robert J. Gillies, Philippe Lambin   +16 more
openalex   +1 more source

Improving Prognostic Performance in Resectable Pancreatic Ductal Adenocarcinoma using Radiomics and Deep Learning Features Fusion in CT Images [PDF]

arXiv, 2019
As an analytic pipeline for quantitative imaging feature extraction and analysis, radiomics has grown rapidly in the past a few years. Recent studies in radiomics aim to investigate the relationship between tumors imaging features and clinical outcomes.
arxiv