Results 101 to 110 of about 6,545,527 (327)

Beyond digital twins: the role of foundation models in enhancing the interpretability of multiomics modalities in precision medicine

FEBS Open Bio, EarlyView.
This review highlights how foundation models enhance predictive healthcare by integrating advanced digital twin modeling with multiomics and biomedical data. This approach supports disease management, risk assessment, and personalized medicine, with the goal of optimizing health outcomes through adaptive, interpretable digital simulations, accessible ...
Sakhaa Alsaedi, Xin Gao, Takashi Gojobori   +2 more
wiley   +1 more source

Deep Projective 3D Semantic Segmentation

, 2017
Semantic segmentation of 3D point clouds is a challenging problem with numerous real-world applications. While deep learning has revolutionized the field of image semantic segmentation, its impact on point cloud data has been limited so far.
AE Johnson, JA Montoya-Zegarra, M Kazhdan, R Szeliski, S Gupta, S Salti, T Hackel   +6 more
core   +1 more source

Revisiting Point Cloud Classification: A New Benchmark Dataset and Classification Model on Real-World Data [PDF]

IEEE International Conference on Computer Vision, 2019
Deep learning techniques for point cloud data have demonstrated great potentials in solving classical problems in 3D computer vision such as 3D object classification and segmentation. Several recent 3D object classification methods have reported state-of-
M. Uy, Quang-Hieu Pham, Binh-Son Hua, D. Nguyen, Sai-Kit Yeung   +4 more
semanticscholar   +1 more source

Evaluating the use of diagnostic CT with flattening filter free beams for palliative radiotherapy: Dosimetric impact of scanner calibration variability

Journal of Applied Clinical Medical Physics, EarlyView.
Abstract Purpose Palliative radiotherapy comprises a significant portion of the radiation treatment workload. Volumetric‐modulated arc therapy (VMAT) improves dose conformity and, in conjunction with flattening filter free (FFF) delivery, can decrease treatment times, both of which are desirable in a population with a high probability of retreatment ...
Madeleine L. Van de Kleut, Lesley A. Buckley, Elsayed S. M. Ali   +2 more
wiley   +1 more source

Effects of Phase Separation Behavior on Morphology and Performance of Polycarbonate Membranes

Membranes, 2017
The phase separation behavior of bisphenol-A-polycarbonate (PC), dissolved in N-methyl-2-pyrrolidone and dichloromethane solvents in coagulant water, was studied by the cloud point method.
Alamin Idris, Zakaria Man, Abdulhalim S. Maulud, Muhammad Saad Khan   +3 more
doaj   +1 more source

Point Cloud GAN

, 2018
Generative Adversarial Networks (GAN) can achieve promising performance on learning complex data distributions on different types of data. In this paper, we first show a straightforward extension of existing GAN algorithm is not applicable to point clouds, because the constraint required for discriminators is undefined for set data.
Li, Chun-Liang, Zaheer, Manzil, Zhang, Yang, Poczos, Barnabas, Salakhutdinov, Ruslan   +4 more
openaire   +2 more sources

Using deep learning generated CBCT contours for online dose assessment of prostate SABR treatments

Journal of Applied Clinical Medical Physics, EarlyView.
Abstract Prostate Stereotactic Ablative Body Radiotherapy (SABR) is an ultra‐hypofractionated treatment where small setup errors can lead to higher doses to organs at risk (OARs). Although bowel and bladder preparation protocols reduce inter‐fraction variability, inconsistent patient adherence still results in OAR variability.
Conor Sinclair Smith, Isabelle Gagne, Karl Otto, Carter Kolbeck, Joshua Giambattista, Abraham Alexander, Sonja Murchison, Andrew Pritchard, Erika Chin   +8 more
wiley   +1 more source

Cloud Point Behavior of Poly(trifluoroethyl methacrylate) in Supercritical CO₂–Toluene Mixtures

Molecules
Supercritical CO2 (scCO2) is a versatile solvent for polymer processing; however, many partially fluorinated polymers exhibit limited solubility in neat scCO2. Organic cosolvents such as toluene can enhance polymer–solvent interactions, thereby improving
James R. Zelaya, Gary C. Tepper
doaj   +1 more source

Relation-Shape Convolutional Neural Network for Point Cloud Analysis [PDF]

Computer Vision and Pattern Recognition, 2019
Point cloud analysis is very challenging, as the shape implied in irregular points is difficult to capture. In this paper, we propose RS-CNN, namely, Relation-Shape Convolutional Neural Network, which extends regular grid CNN to irregular configuration ...
Yongcheng Liu, Bin Fan, Shiming Xiang, Chunhong Pan   +3 more
semanticscholar   +1 more source

Improving dose delivery in non‐coplanar cranial SRS: Stereoscopic x‐ray‐guided mitigation of table walkout errors

Journal of Applied Clinical Medical Physics, EarlyView.
Purpose Linear accelerator (LINAC)‐based single‐isocenter multi‐target (SIMT) treatment has streamlined the cranial stereotactic radiosurgery (SRS) workflow. Though efficient, SIMT delivery adds additional challenges that should be considered, including increased sensitivity to rotational errors for off‐isocenter targets.
Yohan A. Walter, Philip F. Durham, Anne N. Hubbard, William E. Burrell, Hsinshun T. Wu   +4 more
wiley   +1 more source