Results 81 to 90 of about 559,544 (282)
, 2021 For over five decades the procedure termed maximum-entropy (M-E) has been used to sharpen structure in spectra, optical and otherwise. However, this is a contradiction: by modifying data, this approach violates the fundamental M-E principle, which is to extend, in a model-independent way, trends established by low-index Fourier coefficients into the ...
Le, Long V. +3 more
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Molecular Oncology, EarlyView.We developed and validated a DNA methylation–based biomarker panel to distinguish pleural mesothelioma from other pleural conditions. Using the IMPRESS technology, we translated this panel into a clinically applicable assay. The resulting two classifier models demonstrated excellent performance, achieving high AUC values and strong diagnostic accuracy.
Janah Vandenhoeck +12 more
wiley +1 more source
Duality of Maximum Entropy and Minimum Divergence
Entropy, 2014 We discuss a special class of generalized divergence measures by the use of generator functions. Any divergence measure in the class is separated into the difference between cross and diagonal entropy. The diagonal entropy measure in the class associates
Shinto Eguchi +2 more
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Effective therapeutic targeting of CTNNB1‐mutant hepatoblastoma with WNTinib
Molecular Oncology, EarlyView.WNTinib, a Wnt/CTNNB1 inhibitor, was tested in hepatoblastoma (HB) experimental models. It delayed tumor growth and improved survival in CTNNB1‐mutant in vivo models. In organoids, WNTinib outperformed cisplatin and showed enhanced efficacy in combination therapy, supporting its potential as a targeted treatment for CTNNB1‐mutated HB.
Ugne Balaseviciute +17 more
wiley +1 more source
Objective Bayesianism and the Maximum Entropy Principle
Entropy, 2013 Objective Bayesian epistemology invokes three norms: the strengths of our beliefs should be probabilities; they should be calibrated to our evidence of physical probabilities; and they should otherwise equivocate sufficiently between the basic ...
Jon Williamson, Jürgen Landes
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Maximum Entropy and Moment Problems
Real Analysis Exchange, 2004 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
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ATF4‐mediated stress response as a therapeutic vulnerability in chordoma
Molecular Oncology, EarlyView.We screened 5 chordoma cell lines against 100+ inhibitors of epigenetic and metabolic pathways and kinases and identified halofuginone, a tRNA synthetase inhibitor. Mechanistically halofuginone induces an integrated stress response, with eIF2alpha phosphorylation, activation of ATF4 and its target genes CHOP, ASNS, INHBE leading to cell death ...
Lucia Cottone +11 more
wiley +1 more source
Maximum Entropy Learning with Deep Belief Networks
Entropy, 2016 Conventionally, the maximum likelihood (ML) criterion is applied to train a deep belief network (DBN). We present a maximum entropy (ME) learning algorithm for DBNs, designed specifically to handle limited training data.
Payton Lin +4 more
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Molecular Oncology, EarlyView.The cancer problem is increasing globally with projections up to the year 2050 showing unfavourable outcomes in terms of incidence and cancer‐related deaths. The main challenges are prevention, improved therapeutics resulting in increased cure rates and enhanced health‐related quality of life.
Ulrik Ringborg +43 more
wiley +1 more source
Generalized maximum entropy (GME) estimator: formulation and a monte carlo study [PDF]
The origin of entropy dates back to 19th century. In 1948, the entropy concept as a measure of uncertainty was developed by Shannon. A decade after in 1957, Jaynes formulated Shannon’s entropy as a method for estimation and inference particularly for ill-
Eruygur, H. Ozan
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