Results 131 to 140 of about 52,951 (307)

Noninvasive Characterization of Tumor Heterogeneity in HNSCC: From Clinical Utility to Biological Correlates

Advanced Science, EarlyView.
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, Rui Liu, Yuan Zhou, Yin Xiao, Chengmin Feng, Lin Chen, Yanshi Li, Mengna Wang, Zhaobo Cheng, Yuxi Luo, Long Liu, Lijing Niu, Yue Xiang, Juan Peng, Guohua Hu, Min Pan   +15 more
wiley   +1 more source

A Markov Chain Genetic Algorithm Approach for Non-Parametric Posterior Distribution Sampling of Regression Parameters

Algorithms
This paper proposes a genetic algorithm-based Markov Chain approach that can be used for non-parametric estimation of regression coefficients and their statistical confidence bounds.
Parag C. Pendharkar
doaj   +1 more source

Estimation of a multivariate density [PDF]

Annals of the Institute of Statistical Mathematics, 1966
openaire   +1 more source

sparr: Analyzing Spatial Relative Risk Using Fixed and Adaptive Kernel Density Estimation in R [PDF]

The estimation of kernel-smoothed relative risk functions is a useful approach to examining the spatial variation of disease risk. Though there exist several options for performing kernel density estimation in statistical software packages, there have ...
Tilman M. Davies, Jonathan. C Marshall, Martin L. Hazelton   +2 more
core   +1 more source

Artificial Intelligence‐Based Body Composition Analysis Reveals Sex‐Specific Prognostic Markers and Their Clinical Value in Gastric Cancer: A Multicenter Study

Advanced Science, EarlyView.
This study applied AI to quantify multidimensional body composition from CT images in gastric cancer and healthy controls. Distinct sex‐specific patterns and disease‐related alterations were identified and were associated with survival. Higher muscle and fat measures were linked to improved outcomes.
Tianxiang Li, Tingting Liu, Qian Yang, Zhiqing Zhang, Xiaofang Guo, Xiang Wang, Yihan Zhang, Limin Ge, Yu Su, Wenjun Wu, Weihua Guo, Zheng Wang, Lian Yang, Yanfeng Niu   +13 more
wiley   +1 more source

PDIA6–SCD1 Axis Rewires Lipid Metabolism to Drive Gastric Cancer Progression

Advanced Science, EarlyView.
Protein disulfide isomerase A6 (PDIA6) is identified as an oncogenic driver in gastric cancer. PDIA6 directly binds and stabilizes SCD1 by limiting its ubiquitin–proteasome‐mediated degradation, thereby sustaining monounsaturated fatty acid (MUFA)‐enriched lipid homeostasis and lipid metabolic reprogramming.
Zhen Tian, Yifan Cheng, Jiajie Zhou, Ruiqi Li, Shuai Zhao, Ben Li, Zijie Xu, Mengli Zi, Yayan Fu, Chenkai Zhang, Qiannan Sun, Shantanu Baral, Sen Wang, Daorong Wang   +13 more
wiley   +1 more source

Feasible Multivariate Nonparametric Estimation Using Weak Separability [PDF]

One of the main practical problems of nonparametric regression estimation is the curse of dimensionality. The curse of dimensionality arises because nonparametric regression estimates are dependent variable averages local to the point at which the ...
Joris Pinkse
core  

Models and Methods for Automated Background Density Estimation in Hyperspectral Anomaly Detection [PDF]

, 2012
Detecting targets with unknown spectral signatures in hyperspectral imagery has been proven to be a topic of great interest in several applications. Because no knowledge about the targets of interest is assumed, this task is performed by searching the ...
VERACINI, TIZIANA
core  

Circulating Amino Acid Network Remodeling Reveals Systemic Metabolic Reprogramming Predictive of Colorectal Cancer Recurrence and Metastasis

Advanced Science, EarlyView.
Blood‐based amino acid patterns measured by 19F NMR reveal hidden metabolic changes in colorectal cancer. By analyzing how these amino acids interact as a network, machine learning models identify patients at higher risk of recurrence and metastasis.
Ji‐Yeon Lee, Jumi Kim, Taehan Yoon, So Hyun Kwon, Su Chan Park, Dohyun Chun, Dohyeong Kim, Eun Jung Park, Hyunwoo Kim, Ji Min Lee   +9 more
wiley   +1 more source

FFT-Based Probability Density Imaging of Euler Solutions

Entropy
When using traditional Euler deconvolution optimization strategies, it is difficult to distinguish between anomalies and their corresponding Euler tails (those solutions are often distributed outside the anomaly source, forming “tail”-shaped spurious ...
Shujin Cao, Peng Chen, Guangyin Lu, Zhiyuan Ma, Bo Yang, Xinyue Chen   +5 more
doaj   +1 more source