Results 71 to 80 of about 48,979 (300)

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

Deep Learning Network‐Tailored Microenvironment Matching of 4D Bioprinting Bioactive Scaffolds for Bone Regeneration

Advanced Science, EarlyView.
A DLN dataset was built to analyze MABS composition versus in vitro/in vivo osteogenesis and angiogenesis. An MLP neural network, taking BG morphological parameters as input, extracts bioactive features from these datasets. A rabbit tibial defect model then validates 4D‐printed MABS for adaptability and bone regeneration in critical defects.
Xiongjie Liang, Yuechi Zhang, Weifeng Hu, Shiyan Lv, Fan Jia, Yan Zhang, Feng Wu, Changjiang Yang, Guanqi Zhen, Jinglong Yan, Xu Cui, Wei Zhao, Guanghua Chen   +12 more
wiley   +1 more source

Delta-radiomics Entropy Based on Tumor Heterogeneity Concept – Response Predictor to Irradiation for Unresectable/recurrent Glioblastoma [PDF]

, 2022
Although adjuvant radiotherapy in combination with Temozolomide administration has clearly demonstrated the benefit in improving the prognosis of patients with multiforme glioblastoma, radiotherapy as only treatment or in combination with systemic ...
Camil Ciprian MIRESTEAN, Roxana Irina IANCU, Dragos Teodor IANCU   +2 more
core   +2 more sources

Differential Diagnosis of Type 1 and Type 2 Papillary Renal Cell Carcinoma Based on Enhanced CT Radiomics Nomogram

Frontiers in Oncology, 2022
ObjectivesTo construct a contrast-enhanced CT-based radiomics nomogram that combines clinical factors and a radiomics signature to distinguish papillary renal cell carcinoma (pRCC) type 1 from pRCC type 2 tumours.MethodsA total of 131 patients with 60 in
Yankun Gao, Xingwei Wang, Shihui Wang, Yingying Miao, Chao Zhu, Cuiping Li, Guoquan Huang, Yan Jiang, Jianying Li, Xiaoying Zhao, Xingwang Wu   +10 more
doaj   +1 more source

Multiscale Spatial Fusion Feature‐Driven Characterization of Gastric Cancer Invasive Margins: A Multicenter Cohort Study for Preoperative Accurate Differentiation Between T4a and T4b Subtypes

Advanced Science, EarlyView.
This study develops a multi‐dimensional vision Transformer‐based model, GAVR, to accurately distinguish gastric cancer T4a/b stages preoperatively. Validated across multi‐center cohorts, it achieves excellent performance and significantly improves radiologists’ diagnostic accuracy, offering a promising tool for clinical decision‐making.
Guoliang Zheng, Xiaomiao Chai, Peng Jin, Xin Xin, Yingjie Li, Chun Yang, Jia Wei, Zishuo Yan, Jingyu Zhang, Qianning Zhao, Yingchen Han, Ning Zhang, Fuze Li, Bo Qiao, Huan Wang, Huachuan Zheng, Yan Li, Xin Zhang, Yan Zhao, Wenjun Mao, Jing Zhang   +20 more
wiley   +1 more source

Introduction to radiomics for a clinical audience. [PDF]

, 2023
Radiomics is a rapidly developing field of research focused on the extraction of quantitative features from medical images, thus converting these digital images into minable, high-dimensional data, which offer unique biological information that can ...

core   +2 more sources

Alignment of Self‐Supervised Learning Representations With Radiomic Features in Multiphase Renal Computed Tomography

iRADIOLOGY
Background Self‐supervised learning (SSL) has emerged as a promising approach in medical image analysis, offering the ability to learn robust feature representations from unlabeled data. However, the extent to which these embeddings align with clinically
S. J. Pawan, R. Prajwal, Mehrnegar Aminy, Tejal Gala, Matthew Muellner, Xiaomeng Lei, Steven Y. Cen, Inderbir Gill, Mihir Desai, Vinay Duddalwar, Assad A. Oberai   +10 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

Current Status and Challenges of Imaging‐Based Diagnosis of Lymph Node Metastasis in Colon Cancer: The Lymph Node Committee of the Japanese Society for Cancer of the Colon and Rectum

Annals of Gastroenterological Surgery, EarlyView.
This review of the status and challenges of diagnosis of lymph node metastasis in colon cancer suggests that it is currently difficult to establish strict criteria for lymph node metastasis, indicating only moderate diagnostic performance. ABSTRACT Background Accurate pre‐treatment evaluation of lymph node metastasis (LNM) in colon cancer is important ...
Shimpei Ogawa, Yuji Takayama, Yasuyuki Takamizawa, Yukihide Kanemitsu, Hideki Ueno   +4 more
wiley   +1 more source

Engineered molecular diagnostic strategies for hepatocellular carcinoma: Integrating flexible photonic barcodes, liquid biopsies, and AI‐enhanced sensing platforms

FlexMat, EarlyView.
Abstract Early diagnosis of hepatocellular carcinoma (HCC) remains challenging because conventional serum biomarkers, especially alpha‐fetoprotein (AFP), show limited sensitivity for early‐stage disease. Recent progress in engineered molecular diagnostics provides new opportunities to improve HCC detection through integrated material, molecular, and ...
Jingzhi Xue, Wanqi Yang, Xiaoyu Liu, Xuehui Chu, Wei Li, Jinglin Wang   +5 more
wiley   +1 more source