Results 61 to 70 of about 510,572 (297)

In vitro models of cancer‐associated fibroblast heterogeneity uncover subtype‐specific effects of CRISPR perturbations

Molecular Oncology, EarlyView.
Development of therapies targeting cancer‐associated fibroblasts (CAFs) necessitates preclinical model systems that faithfully represent CAF–tumor biology. We established an in vitro coculture system of patient‐derived pancreatic CAFs and tumor cell lines and demonstrated its recapitulation of primary CAF–tumor biology with single‐cell transcriptomics ...
Elysia Saputra, Shamsudheen Karuthedath Vellarikkal, Lixia Li, Hong Sun, Khoa Nguyen, Amber Montano, Suchitra Natarajan, Federica Piccioni, Alex Michael Tamburino, Xin Yu, Aleksandra Katarzyna Olow   +10 more
wiley   +1 more source

Dual targeting of RET and SRC synergizes in RET fusion‐positive cancer cells

Molecular Oncology, EarlyView.
Despite the strong activity of selective RET tyrosine kinase inhibitors (TKIs), resistance of RET fusion‐positive (RET+) lung cancer and thyroid cancer frequently occurs and is mainly driven by RET‐independent bypass mechanisms. Son et al. show that SRC TKIs significantly inhibit PAK and AKT survival signaling and enhance the efficacy of RET TKIs in ...
Juhyeon Son, Lily L. Remsing Rix, Bin Fang, Eric A. Welsh, Nicole V. Bremer, Valentina Foglizzo, Paola Roa, Nickole Sigcha‐Coello, Yi Liao, Eric B. Haura, Alexander Drilon, John M. Koomen, Emiliano Cocco, Uwe Rix   +13 more
wiley   +1 more source

Learning unbiased features

, 2014
A key element in transfer learning is representation learning; if representations can be developed that expose the relevant factors underlying the data, then new tasks and domains can be learned readily based on mappings of these salient factors. We propose that an important aim for these representations are to be unbiased.
Li, Yujia, Swersky, Kevin, Zemel, Richard   +2 more
openaire   +2 more sources

Methylation biomarkers can distinguish pleural mesothelioma from healthy pleura and other pleural pathologies

Molecular Oncology, EarlyView.
We developed and validated a DNA methylation–based biomarker panel to distinguish pleural mesothelioma from other pleural conditions. Using the IMPRESS technology, we translated this panel into a clinically applicable assay. The resulting two classifier models demonstrated excellent performance, achieving high AUC values and strong diagnostic accuracy.
Janah Vandenhoeck, Nele De Meulenaere, Thomas Vanpoucke, Joe Ibrahim, Dieter Peeters, Suresh Krishan Yogeswaran, Wen Wen, Paul Van Schil, Jeroen M. H. Hendriks, Jo Raskin, Jan van Meerbeeck, Guy Van Camp, Ken Op de Beeck   +12 more
wiley   +1 more source

Perspectives in educating molecular pathologists on liquid biopsy: Toward integrative, equitable, and decentralized precision oncology

Molecular Oncology, EarlyView.
Liquid biopsy enables minimally invasive, real‐time molecular profiling through analysis of circulating biomarkers in biological fluids. This Perspective highlights the importance of training pathologists through integrative educational programs, such as the European Masters in Molecular Pathology, to ensure effective and equitable implementation of ...
Marius Ilié, Umberto Malapelle, Catherine Alix‐Panabières, Claus Lindbjerg Andersen, Sandra Chlebowski, Vivien Lake, Caroline Lacoux, Virginie Lespinet‐Fabre, Olivier Bordone, Simon Heeke, Christophe Bontoux, Ellen Heitzer, Klaus Pantel, Paul Hofman   +13 more
wiley   +1 more source

Compact Dominant Synergistic Excitation Pattern Learning for Illumination-Insensitive Image Representation With Boosting

IEEE Access, 2019
Illumination-insensitive image representation is a great challenge in the computer vision field. Illumination variations considerably obstruct the effectiveness of image feature extraction.
Tao Gao, Ting Chen, C. C. Wang, Zhanwen Liu, Wei Lu, Y. H. Li   +5 more
doaj   +1 more source

Video Tracking Using Learned Hierarchical Features [PDF]

IEEE Transactions on Image Processing, 2015
In this paper, we propose an approach to learn hierarchical features for visual object tracking. First, we offline learn features robust to diverse motion patterns from auxiliary video sequences. The hierarchical features are learned via a two-layer convolutional neural network.
Wang, Gang, Chan, Kap Luk, Liu, Ting, Yang, Qingxiong, Wang, Li   +4 more
openaire   +3 more sources

Next‐generation proteomics improves lung cancer risk prediction

Molecular Oncology, EarlyView.
This is one of very few studies that used prediagnostic blood samples from participants of two large population‐based cohorts. We identified, evaluated, and validated an innovative protein marker model that outperformed an established risk prediction model and criteria employed by low‐dose computed tomography in lung cancer screening trials.
Megha Bhardwaj, Clara Frick, Ben Schöttker, Bernd Holleczek, Hermann Brenner   +4 more
wiley   +1 more source

Locally Shared Features: An Efficient Alternative to Conditional Random Field for Semantic Segmentation

IEEE Access, 2019
In recent years, semantic segmentation methods based on fully convolutional networks (FCNs) have achieved great success. However, these methods tend to produce inconsistency and isolated class labels, mainly because the end-to-end mapping of FCN ...
Zhengeng Yang, Hongshan Yu, Wei Sun, Zhihong Mao, Mingui Sun   +4 more
doaj   +1 more source

Feature Reinforcement Learning in Practice [PDF]

, 2012
Following a recent surge in using history-based methods for resolving perceptual aliasing in reinforcement learning, we introduce an algorithm based on the feature reinforcement learning framework called PhiMDP. To create a practical algorithm we devise a stochastic search procedure for a class of context trees based on parallel tempering and a ...
Nguyen, Phuong, Sunehag, Peter, Hutter, Marcus   +2 more
openaire   +3 more sources