Beam Stacking Experiments in an Electron Model FFAG Accelerator
K. M. Terwilliger+2 more
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Prostate cancer is a leading malignancy with significant clinical heterogeneity in men. An 11‐gene signature derived from dysregulated epithelial cell markers effectively predicted biochemical recurrence‐free survival in patients who underwent radical surgery or radiotherapy.
Zhuofan Mou, Lorna W. Harries
wiley +1 more source
Machine learning in prediction of epidermal growth factor receptor status in non-small cell lung cancer brain metastases: a systematic review and meta-analysis. [PDF]
Hajikarimloo B+9 more
europepmc +1 more source
Clinical significance of stratifying prostate cancer patients through specific circulating genes
We tested a specific panel of genes representative of luminal, neuroendocrine and stem‐like cells in the blood of prostate cancer patients, showing predictive value from diagnosis to late stages of disease. This approach allows monitoring of treatment responses and outcomes at specific time points in trajectories.
Seta Derderian+12 more
wiley +1 more source
Target-Controlled Infusion of Propofol: A Systematic Review of Recent Results. [PDF]
Šafránková P, Bruthans J.
europepmc +1 more source
Some elementary topological properties of essential maximal model continua [PDF]
W. R. Scott
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MET variants in the N‐lobe of the kinase domain, found in hereditary papillary renal cell carcinoma, require ligand stimulation to promote cell transformation, in contrast to other RTK variants. This suggests that HGF expression in the microenvironment is important for tumor growth in such patients. Their sensitivity to MET inhibitors opens the way for
Célia Guérin+14 more
wiley +1 more source
Comparison of machine learning models with conventional statistical methods for prediction of percutaneous coronary intervention outcomes: a systematic review and meta-analysis. [PDF]
Nayebirad S+6 more
europepmc +1 more source
Errata: Electronic Interaction in the Free-Electron Network Model for Conjugated Systems. I. Theory [PDF]
Norman S. Ham, Klaus Ruedenberg
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