Results 141 to 150 of about 73,359 (292)

Multiparametric MRI to Predict Response to Irreversible Electroporation Plus Anti‐PD‐1 Immunotherapy in Pancreatic Ductal Adenocarcinoma

Magnetic Resonance in Medicine, Volume 95, Issue 4, Page 2266-2276, April 2026.
ABSTRACT Purpose To investigate contrast‐enhanced T1‐weighted MRI and diffusion‐weighted magnetic resonance imaging (DWI) for early prediction of tumor response to combined irreversible electroporation (IRE) and anti‐PD‐1 immunotherapy. Methods Murine pancreatic ductal adenocarcinoma (PDAC) cells KRAS* were inoculated into the pancreas of C57BL/6 mice.
Qizhen Cao, Mark D. Pagel, Charles V. Kingsley, Jingfei Ma, James P. Long, Xiaoxia Wen, Seth T. Gammon, Jorge Delacerda, Sanaz Javadi, Chun Li   +9 more
wiley   +1 more source

A Bounding Box-Based Radiomics Model for Detecting Occult Peritoneal Metastasis in Advanced Gastric Cancer: A Multicenter Study

, 2021
Dan Liu, Weihan Zhang, Fubi Hu, Pengxin Yu, Xiao Zhang, Hongkun Yin, Lanqing Yang, Xin Fang, Bin Song, Bing Wu, Jian-Kun Hu, Zixing Huang   +11 more
openalex   +1 more source

Evaluating the impact of deep learning‐based image denoising on low‐dose CT for lung cancer screening

Journal of Applied Clinical Medical Physics, Volume 27, Issue 2, February 2026.
Abstract Purpose Low‐dose CT (LDCT) is increasingly being adopted as a preferred method for lung cancer screening. However, the accompanying rise in image noise necessitates robust denoising strategies. Therefore, this study compared LDCT images with their denoised counterparts using objective image quality metrics and key nodule‐related features ...
Shih‐Sheng Chen, Hsiao‐Hua Liu, Ching‐Ching Yang   +2 more
wiley   +1 more source

A study on the value of ultrasound strain elastography-based radiomics nomogram in the differential diagnosis of breast masses

Scientific Reports
The aim of this study was to construct a radiomics nomogram for prediction of breast masses (BMs) by analyzing the clinical characteristics of the patients as well as radiomics features of two-dimensional (2D) ultrasound images and strain elastography ...
Yunpei Zhu, Yanping Dou, Qifan Hu, Hui Wang   +3 more
doaj   +1 more source

Radiomics-Based Support Vector Machine Distinguishes Molecular Events Driving the Progression of Lung Adenocarcinoma [PDF]

Hongji Li, Zhen‐Bin Qiu, Meng-Min Wang, Chao Zhang, Hui-Zhao Hong, Rui Fu, Lishan Peng, Chen Huang, Qian Cui, Jia-Tao Zhang, Jingyun Ren, Lei Jiang, Yi‐Long Wu, Wen-Zhao Zhong   +13 more
openalex   +1 more source

AI and Big Data in Oncology: A Physician‐Centered Perspective on Emerging Clinical and Research Applications

Cancer Innovation, Volume 5, Issue 1, February 2026.
Artificial intelligence and big data platforms are transforming oncology clinical practice. This review proposes a physician‐centered framework to integrate AI tools with real‐world data, supporting more precise diagnosis, individualized treatment, and improved patient outcomes.
Binliang Liu, Qingyao Shang, Jun Li, Shuna Yao, Meishuo Ouyang, Yu Wang, Sheng Luo, Quchang Ouyang   +7 more
wiley   +1 more source

Radiomic tumor phenotypes augment molecular profiling in predicting recurrence free survival after breast neoadjuvant chemotherapy

, 2023
Rhea Chitalia, Marios Miliotis
openalex   +2 more sources

Bispecific Antibodies Versus Chimeric Antigen Receptor T‐Cell Therapy in Relapsed/Refractory Diffuse Large B‐Cell Lymphoma: A Comparative Narrative Review of Efficacy, Safety, and Accessibility

Cancer Medicine, Volume 15, Issue 2, February 2026.
ABSTRACT Introduction Diffuse large B‐cell lymphoma (DLBCL) is the most common subtype of non‐Hodgkin lymphoma, and despite advances in frontline therapies such as rituximab, cyclophosphamide, doxorubicin hydrochloride (hydroxydaunorubicin), vincristine sulfate (Oncovin), and prednisone, approximately 30%–40% of patients develop relapsed or refractory (
Dana Sofian Abou, Husna Irfan Thalib, Fayza Akil, Samia Zuhair Sabbagh, Hala Sofian Abou, Mable Pereira, Fatma ElSayed Hassan   +6 more
wiley   +1 more source

The clinical implications and interpretability of computational medical imaging (radiomics) in brain tumors

Insights into Imaging
Radiomics has widespread applications in the field of brain tumor research. However, radiomic analyses often function as a ‘black box’ due to their use of complex algorithms, which hinders the translation of brain tumor radiomics into clinical ...
Yixin Wang, Zongtao Hu, Hongzhi Wang
doaj   +1 more source

Comparative analysis of machine learning models for predicting pathological complete response to neoadjuvant chemotherapy in breast cancer: An MRI radiomics approach [PDF]

Alessia D’Anna, Carlo Aranzulla, Carlo Carnaghi, Francesco Caruso, Gaetano Castiglione, Roberto Grasso, Anna Maria Gueli, C. Marino, F. Pane, Alfredo Pulvirenti, Giuseppe Stella   +10 more
openalex   +1 more source