Results 81 to 90 of about 1,793,798 (289)
Molecular Oncology, EarlyView.In the present work, we have identified a transcriptional signature based on the differential expression of six genes (BCL2&MAST4, HSH2D&LAT2, METRN&PITPNM2) that would facilitate the early detection of T‐cell acute lymphoblastic leukemia (T‐ALL) patients prone to a poor treatment response and could be implemented at diagnosis, along with other risk ...
Antonio Lahera +11 more
wiley +1 more source
Feature name and associated ranking.
, 2020 Feature name and associated ranking.
Md. Raihan-Al-Masud (8415444) +1 more
core +1 more source
Ranking Feature Importance Objectives for Explainable Classification
IEEE AccessRecent studies on explainable machine learning models often analyse feature importance after training, but this results in a model that does not capture feature dependencies and requires extra computational resources for explainability.
Pragya Gupta +4 more
doaj +1 more source
KDM7A and KDM1A inhibition suppresses tumour promoting pathways in prostate cancer
Molecular Oncology, EarlyView.Treatment resistance is a major challenge for patients with advanced prostate cancer. This study examined an alternative approach to target the major prostate cancer‐promoting pathway by targeting epigenetic factors, whose levels are higher in tumours.
Jennie N Jeyapalan +16 more
wiley +1 more source
Feature Ranking for Predicting Occupant Visual Comfort in University Laboratories Using Machine Learning [PDF]
E3S Web of ConferencesVisual comfort is crucial for both occupant well-being and energy efficiency in smart buildings in university laboratory settings. While AI-driven urban sustainability has seen advances, there is little work on visual comfort in university laboratories ...
Al Shafik Md. Fardin +2 more
doaj +1 more source
A Matlab Toolbox for Feature Importance Ranking [PDF]
2019 International Conference on Medical Imaging Physics and Engineering (ICMIPE), 2019 More attention is being paid for feature importance ranking (FIR), in particular when thousands of features can be extracted for intelligent diagnosis and personalized medicine. A large number of FIR approaches have been proposed, while few are integrated for comparison and real-life applications.
Shaode Yu +6 more
openaire +2 more sources
Molecular Oncology, EarlyView.RNA profiling of circulating extracellular vesicles (EVs) from blood samples of men undergoing prostate biopsy identifies transcripts associated with clinically significant prostate cancer. Integrative analysis with public tumor datasets links EV‐derived gene signatures to tumor stage and progression‐free survival, highlighting CASP3, XRCC2, and RIT1 ...
Stefan Werner +14 more
wiley +1 more source
Molecular Oncology, EarlyView.This study shows that lung adenocarcinomas exploit developmental branching morphogenesis to acquire a therapy resistant basal‐like tumour cell state. This process was found to be regulated by combined TP53 loss‐of‐function and type‐I interferon signalling, identifying a novel axis for biomarker and therapeutic target discovery.
Kamila J Bienkowska +13 more
wiley +1 more source
Ranking to Learn: Feature Ranking and Selection via Eigenvector Centrality
CoRR, 2017 In an era where accumulating data is easy and storing it inexpensive, feature selection plays a central role in helping to reduce the high-dimensionality of huge amounts of otherwise meaningless data. In this paper, we propose a graph-based method for feature selection that ranks features by identifying the most important ones into arbitrary set of ...
Roffo Giorgio, Melzi Simone
openaire +3 more sources
Feature Importance Ranking for Deep Learning
CoRR, 2020 Accepted by NeurIPS 2020, 5 Figures and 1 Table in Main text, 10 Figures and 5 Tables in Supplementary ...
Wojtas, Maksymilian +1 more
openaire +5 more sources