Results 111 to 120 of about 2,243,062 (248)
Towards Fair Graph Neural Networks via Counterfactual and Balance
In recent years, graph neural networks (GNNs) have shown powerful performance in processing non-Euclidean data. However, similar to other machine-learning algorithms, GNNs can amplify data bias in high-risk decision-making systems, which can easily lead ...
Zhiguo Xiao +3 more
doaj +1 more source
Practical Bias Mitigation through Proxy Sensitive Attribute Label Generation
Addressing bias in the trained machine learning system often requires access to sensitive attributes. In practice, these attributes are not available either due to legal and policy regulations or data unavailability for a given demographic. Existing bias
Bhatt, Deepak +3 more
core
Circulating microRNA profiles distinguish nonmalignant Lynch syndrome from cancer‐associated Lynch syndrome, sporadic colorectal cancer, and healthy controls. Age‐stratified analysis reveals disease‐specific regulatory states, and a six‐miRNA panel shows concordant separation in an independent colorectal tissue cohort.
Ramadhani Salum Chambuso +5 more
wiley +1 more source
RANGE AND NUMBER-OF-LEVELS EFFECTS IN DERIVED AND STATED MEASURES OF ATTRIBUTE IMPORTANCE [PDF]
We study how the range of variation and the number of attribute levels affect five measures of attribute importance: full profile conjoint estimates, ranges in attribute level attractiveness ratings, regression coefficients, graded paired comparisons ...
Wittink, Dick R. +2 more
core
The kinase SRPK1 directly interacts with the protein TOPBP1 and regulates the pre‐mRNA splicing of WIZ thereby contributing to the activation of the ATR/CHK1 replicative checkpoint in response to replicative stress. This allows cancer cells' genomic stability and survival.
Amani Shreim +17 more
wiley +1 more source
Spatial heterogeneity of hotspot mutations and clonal relatedness in ovarian endometrioid carcinoma
Spatially resolved analysis revealed heterogeneous distributions of selected cancer‐associated mutations within ovarian endometrioid carcinomas. Shared mutations between paired endometrial and ovarian tumors supported clonal relatedness. These findings highlight the value of sampling multiple tumor regions when interpreting molecular profiles ...
Takahito Ashihara +10 more
wiley +1 more source
Multi-Scale Convolutional VAE for Anomaly Detection in Sensitive Power Marketing Data
Anomalous sensitive power marketing data can significantly impact the interests of various stakeholders in the development of power enterprises. To improve anomaly detection in such data, we propose a method based on the Multi-Scale Convolutional ...
Jinkai Sun, Chun Xiao, Junfeng Yao
doaj +1 more source
The multifaceted roles of lysosomes in cancer
Lysosomes support cancer cell adaptation by integrating macromolecule degradation and nutrient recycling with nutrient sensing, inter‐organelle communication and immune regulation. These interconnected functions can promote tumour growth, stress tolerance and therapy resistance, while also creating context‐dependent vulnerabilities that may be ...
Jia Li, Kevin M. Ryan
wiley +1 more source
Tumour‐proximal deep serum proteomics identifies biomarkers associated with ovarian cancer
New biomarkers are needed for early ovarian cancer detection. Ovarian (tumour‐proximal) and peripheral vein serum from healthy women and patients with benign or malignant tumours underwent nanoparticle‐enriched deep proteomics. Ovarian serum yielded more protein identifications and revealed tumour‐reflective signatures.
Darren Lau +9 more
wiley +1 more source
Attitudes of cancer patients toward ctDNA‐based liquid biopsy for follow‐up
This mixed‐methods study explored cancer patients' experiences, knowledge, and preferences regarding ctDNA‐based liquid biopsy for follow‐up. Awareness of ctDNA was low and recall of previous liquid biopsy was imperfect, yet acceptance was high.
Siddharth Chhajlani +7 more
wiley +1 more source

