Results 181 to 190 of about 43,566 (284)

Development and validation of an interpretable ultrasound radiomics model for benign and malignant classification of breast lesions: a multicenter large-sample study. [PDF]

Insights Imaging
Zhang D, Lu WW, Qin XC, Zhou W, Zhang XY, Luo YH, Wu LS, Wu J, Wang JL, Zhao JJ, Zhang L, Zhang CX.   +11 more
europepmc   +1 more source

Probabilistic quality assurance of biopsy DVH thresholds in HDR prostate brachytherapy under localization uncertainty

Journal of Applied Clinical Medical Physics, Volume 27, Issue 8, August 2026.
Abstract Background MR‐US guided biopsies support biologic correlation in HDR prostate brachytherapy, but steep dose gradients and millimeter‐scale localization uncertainty limit the validity of nominal biopsy doses. Purpose To assess how localization uncertainty affects the robustness of biopsy DVH dose thresholds in HDR prostate brachytherapy and to ...
Matthew Muscat, Juanita Crook, Andrew Jirasek, Jeffrey Andrews, Nathan Becker   +4 more
wiley   +1 more source

Beyond the naked eye: a systematic review on the current state of radiomics approaches to the vestibular schwannoma. [PDF]

J Neurooncol
Gundlapalli R, Ramanathan P, Akula V, Fox D, Nguyen M, Meyers D, He X, Ishaque M, Kellogg RT, Lovin BD, Sheehan J, Thompson-Harvey A, Maragkos G, Asthagiri A.   +13 more
europepmc   +1 more source

Estimation of pulmonary function from time‐resolved dynamic chest radiography using machine learning in patients with respiratory disease

Journal of Applied Clinical Medical Physics, Volume 27, Issue 8, August 2026.
Abstract Background Pulmonary function tests (PFTs), particularly spirometry, are the reference standard for assessing airflow limitation in respiratory diseases such as chronic obstructive pulmonary disease (COPD) and interstitial pulmonary disease.
Takehiro Shiinoki, Yuki Yuasa, Tsunahiko Hirano, Maki Asami‐Noyama, Kazuto Matsunaga, Hidekazu Tanaka   +5 more
wiley   +1 more source

Radiomics-Based Prediction of Microvascular Invasion Grade in Nodular Hepatocellular Carcinoma Using Contrast-Enhanced Magnetic Resonance Imaging [PDF]

Zhao Zhang, Xiu-Fen Jia, Xiao-Yu Chen, Yong-Hua Chen, Ke-Hua Pan Department of Radiology, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, 325000, People’s Republic of ChinaCorrespondence: Ke-Hua Pan, Department of Radiology, The ...
Zhang Z, Jia XF, Chen XY, Chen YH, Pan KH   +4 more
core   +1 more source

Development and Validation of a Multi-Omics Model Integrating US-Derived and WSI-Based Features to Predict Lymph Node Metastasis in Ovarian Cancer: A Multi-Center Retrospective Study. [PDF]

Int J Womens Health
Yan G, Wu X, Zhao P, Zhou F, Xu S, Yao M, Ji Y, Li J, Feng Q, Zhao L, Du H.   +10 more
europepmc   +1 more source

Obese patient imaging: Potential dose reduction with photon‐counting CT

Journal of Applied Clinical Medical Physics, Volume 27, Issue 8, August 2026.
Abstract Background Photon‐counting CT (PCCT) offers key advantages over energy integrating detector CT (EID‐CT), especially in low‐dose scans and imaging larger patients. As obesity rates rise, minimizing image noise is critical for diagnostic accuracy.
Leening P. Liu, Kai Mei, Shobhit Sharma, Steven Ross, Sandra S. Halliburton, Richard Thompson, Naruomi Akino, Ali H. Dhanaliwala, Leonid Roshkovan, Harold I. Litt, Peter B. Noël   +10 more
wiley   +1 more source

Radiomics-Guided Multi-Sequence Learning for Pathological Complete Response Prediction from Breast MRI with Missing Auxiliary Sequences. [PDF]

J Imaging
Xiang X, Yin W, Li J.
europepmc   +1 more source

The Quest for Generalizability in Radiomics

Radiology: Artificial Intelligence, 2020
openaire   +3 more sources

Machine Learning‐Based Prediction of Poor Outcomes in Intracerebral Hemorrhage: A Systematic Review and Meta‐Analysis

Brain and Behavior, Volume 16, Issue 8, August 2026.
ABSTRACT Background Spontaneous intracerebral hemorrhage (ICH) is associated with high risks of mortality and disability, yet early and accurate outcome prediction remains challenging. This study systematically evaluated the performance of machine learning (ML) models in predicting key adverse outcomes (hematoma expansion [HE], poor functional outcome,
Qi Deng, Weitao Cheng, Hui Lu, Nan Fei, Rong He, Yuanyuan Chen, Jianlong Bi, Wenluo Zhang   +7 more
wiley   +1 more source