Results 81 to 90 of about 102,167 (290)
Data-Driven Structuring of the Output Space Improves the Performance of Multi-Target Regressors
The task of multi-target regression (MTR) is concerned with learning predictive models capable of predicting multiple target variables simultaneously. MTR has attracted an increasing attention within research community in recent years, yielding a variety
Stevanche Nikoloski +2 more
doaj +1 more source
Loss of the miR‐214/199a cluster is associated with recurrence in ovarian cancer. Engineered small extracellular vesicles (m214‐sEVs) elevate miR‐214‐3p/miR‐199a‐5p in tumor cells, suppress β‐catenin, TLR4, and YKT6 signaling, reprogram tumor‐derived sEV cargo, reduce chemoresistance and migration, and enhance carboplatin efficacy and survival in ...
Weida Wang +12 more
wiley +1 more source
Interrogating the immune landscape of microsatellite stable RAS‐mutated colon cancer
COLOSSUS project RAS‐mutated MSS colon cancer study explored transcriptomics and immune cell density by immunohistochemistry (IHC), Immunoscore (IS), ISIC/TuLIS scores, mutation counts, and detected different prevalences but similar microenvironment composition across immune markers with clinical relevance for future immunotherapy combination ...
Rodrigo Dienstmann +61 more
wiley +1 more source
Multivariate feature ranking of gene expression data
Gene expression datasets are usually of high dimensionality and therefore require efficient and effective methods for identifying the relative importance of their attributes.
Sánchez, Gracia +4 more
core
Keratin 19 (KRT19) is overexpressed in high‐grade serous ovarian cancer with high levels of Kallikrein‐related peptidases (KLK) 4–7 and is associated with poor survival. In vivo analyses demonstrate that elevated KRT19 increases peritoneal tumour burden.
Sophia Bielesch +13 more
wiley +1 more source
Interpretability is crucial for the clinical adoption of machine learning, as healthcare providers require transparent decision-making processes to trust predictive tools effectively. Traditional feature selection methods often struggle to capture subtle
Daniel Pordeus +3 more
doaj +1 more source
We have established a humanized orthotopic patient‐derived xenograft (Hu‐oPDX) mouse model of high‐grade serous ovarian cancer (HGSOC) that recapitulates human tumor–immune interactions. Using combined anti‐PD‐L1/anti‐CD73 immunotherapy, we demonstrate the model's improved biological relevance and enhanced translational value for preclinical ...
Luka Tandaric +10 more
wiley +1 more source
Ranking to Learn: Feature Ranking and Selection via Eigenvector Centrality
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
Pancreatic sensory neurons innervating healthy and PDAC tissue were retrogradely labeled and profiled by single‐cell RNA sequencing. Tumor‐associated innervation showed a dominant neurofilament‐positive subtype, altered mitochondrial gene signatures, and reduced non‐peptidergic neurons.
Elena Genova +14 more
wiley +1 more source
LLM feature ranking for the impaired QoL class in the three cases. (A): all group; (B): controlled asthma group; (C): Not controlled asthma group.
Maurizio Mongelli (14134888) +3 more
core +1 more source

