Results 231 to 240 of about 68,766 (311)
Real space iterative reconstruction for vector tomography (RESIRE-V). [PDF]
Pham M, Lu X, Rana A, Osher S, Miao J.
europepmc +1 more source
A biomimetic artificial intelligence system, PancDS, has been developed to distinguish pancreatic ductal adenocarcinoma from mass‐forming pancreatitis by adaptively integrating clinical data, radiomics, and deep learning features. Validated across multicenter, reader‐study, and prospective settings, PancDS improves diagnostic accuracy, particularly for
Zhibo Wang +13 more
wiley +1 more source
Noise Reduction in Brain CT: A Comparative Study of Deep Learning and Hybrid Iterative Reconstruction Using Multiple Parameters. [PDF]
Inoue Y +6 more
europepmc +1 more source
A unique mechanism of catalytic bias regulated by diaphorase‐like subunit in formate dehydrogenase from Rhodobacter aestuarii is revealed. The diaphorase‐like subunit functions act as a biological “voltage rheostat” that controls the slow release of NADH to regulate redox balance, biasing the enzyme's catalytic preference toward CO2 reduction over ...
Kuncheng Zhang +7 more
wiley +1 more source
Reduced-dose deep learning iterative reconstruction for abdominal computed tomography with low tube voltage and tube current. [PDF]
Zhu S +13 more
europepmc +1 more source
This study establishes a CT‐based radiomics framework to quantify intratumoral heterogeneity (ITH) in HNSCC. Using unsupervised clustering, tumor ROIs and VOIs are analyzed to calculate 2D/3D ITH scores. The score shows strong predictive value for prognosis and immunotherapy response, and is associated with tumor metabolism and immune microenvironment,
Xinwei Chen +15 more
wiley +1 more source
Generative priors-constraint accelerated iterative reconstruction for extremely sparse photoacoustic tomography boosted by mean-reverting diffusion model: Towards 8 projections. [PDF]
Lian T +9 more
europepmc +1 more source
This review explores the convergence of artificial intelligence technologies in modeling drug–drug and drug–target interactions. By evaluating advanced feature engineering, architectural innovations, and learning paradigms reveals shared evolutionary trends and critical challenges, such as cold‐start settings and shortcut learning.
Xin Sun, Tong Wang
wiley +1 more source
Deep Learning-Based Super-Resolution Reconstruction on Undersampled Brain Diffusion-Weighted MRI for Infarction Stroke: A Comparison to Conventional Iterative Reconstruction. [PDF]
Zhang S +12 more
europepmc +1 more source

