Results 61 to 70 of about 73,359 (292)

Prediction of PD-L1 and CD68 in Clear Cell Renal Cell Carcinoma with Green Learning

Journal of Imaging
Clear cell renal cell carcinoma (ccRCC) is the most common type of renal cancer. Extensive efforts have been made to utilize radiomics from computed tomography (CT) imaging to predict tumor immune microenvironment (TIME) measurements. This study proposes
Yixing Wu, Alexander Shieh, Steven Cen, Darryl Hwang, Xiaomeng Lei, S. J. Pawan, Manju Aron, Inderbir Gill, William D. Wallace, C.-C. Jay Kuo, Vinay Duddalwar   +10 more
doaj   +1 more source

Towards reproducible radiomics research: introduction of a database for radiomics studies

European Radiology, 2023
Abstract Objectives To investigate the model-, code-, and data-sharing practices in the current radiomics research landscape and to introduce a radiomics research database. Methods A total of 1254 articles published between January 1, 2021, and December 31, 2022, in leading ...
Akinci D'Antonoli, Tugba, Cuocolo, Renato, Baessler, Bettina, Pinto Dos Santos, Daniel   +3 more
openaire   +4 more sources

Immune Predictors of Radiotherapy Outcomes in Cervical Cancer

Advanced Science, EarlyView.
This study reveals dynamic immune remodeling in cervical cancer following radiotherapy. Single‐cell analysis identifies the C3/C3AR1 axis as a central mediator of epithelial–myeloid crosstalk, whose inhibition reduces treatment efficacy in mice. Guided by these insights, the eight‐feature machine‐learning model: Cervical Cancer Radiotherapy Immune ...
Linghao Wang, Jie Zhu, Zequn Ding, Zhiyuan Xie, Xingchen Liu, Feihong Zhang, Xiaojun Liu, Yan Zhang, Haiyan Chen   +8 more
wiley   +1 more source

Value of 18F-FDG-PET/CT radiomics combined with clinical variables in the differential diagnosis of malignant and benign vertebral compression fractures

EJNMMI Research, 2023
Background Vertebral compression fractures (VCFs) are common clinical problems that arise from various reasons. The differential diagnosis of benign and malignant VCFs is challenging.
Xun Wang, Dandan Zhou, Yu Kong, Nan Cheng, Ming Gao, Guqing Zhang, Junli Ma, Yueqin Chen, Shuang Ge   +8 more
doaj   +1 more source

Discrimination of benign and malignant non-mass breast lesions using ultrasound radiomics with machine learning models. [PDF]

J Appl Clin Med Phys
Abstract Aims This study aims to enhance the preoperative diagnosis of non‐mass breast lesions (NMLs) by validating radiomics‐based machine learning models and assessing their performance alone and in combination with clinical ultrasound features to distinguish benign from malignant lesions.
Shi C, He H, Chen B, Lu J, Xu Q, Zhao K, Yang X.   +6 more
europepmc   +2 more sources

MR‐DELTAnet: A Longitudinal MRI‐Transformer Model Predicting Pathological Complete Response and Revealing Immune Microenvironment via scRNA‐seq in Locally Advanced Rectal Cancer

Advanced Science, EarlyView.
The MR‐DELTAnet model utilizes longitudinal MRI to predict treatment response after neoadjuvant chemoradiotherapy in locally rectal cancer patients, accurately identifying patients likely to achieve pathological complete response for personalized management.
Wuteng Cao, Huaxian Chen, Jiao Li, Yihui Zheng, Liqing Xie, Guozhong Xiao, Zeyan Wang, Fen Yuan, Junhong Chen, Chongbao Sun, Jing Dai, Jinping Zeng, Xinhua Wang, Lei Wu, Hongcheng Lin   +14 more
wiley   +1 more source

Radiomics: a critical step towards integrated healthcare [PDF]

Insights into Imaging, 2018
Medical imaging is a vital part of the clinical decision-making process, especially in an oncological setting. Radiology has experienced a great wave of change, and the advent of quantitative imaging has provided a unique opportunity to analyse patient images objectively.
Bodalal, Zuhir, Trebeschi, Stefano, Beets-Tan, Regina   +2 more
openaire   +4 more sources

Photoacoustic Microscopy for Multiscale Biological System Visualization and Clinical Translation

Advanced Science, EarlyView.
Photoacoustic microscopy (PAM) is a powerful biomedical imaging tool renowned for its non‐invasiveness and high resolution. This review synthesizes recent technological advances and highlights their broad applications from cellular and organ‐level to whole‐animal imaging.
Tingting Wang, Jiali Chen, Liming Nie, Honghui Li   +3 more
wiley   +1 more source

Machine Learning Model Integrating CT Radiomics of the Lung to Predict Checkpoint Inhibitor Pneumonitis in Patients with Advanced Cancer

Technology in Cancer Research & Treatment
Objective Checkpoint inhibitor pneumonitis (CIP) is a potentially life-threatening immune-related adverse event. Efficient strategies to select patients at risk are still required.
François Cousin MD, PhD, Thomas Louis MS, PhD, Pierre Frères MD, PhD, Julien Guiot MD, PhD, Mariaelena Occhipinti MD, Fabio Bottari MS, Wim Vos MS, Roland Hustinx MD, PhD   +7 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   +1 more source