Results 61 to 70 of about 1,212,947 (298)
Implementation of mutual information and bayes theorem for classification microarray data
, 2018 Microarray Technology is one of technology which able to read the structure of gen. The analysis is important for this technology. It is for deciding which attribute is more important than the others.
Mahendra Dwifebri +5 more
semanticscholar +1 more source
From Droplet to Diagnosis: Spatio‐Temporal Pattern Recognition in Drying Biofluids
Advanced Intelligent Systems, EarlyView.This article integrates machine learning (ML) with the spatio‐temporal evolution of biofluid droplets to reveal how drying and self‐assembly encode distinctive compositional fingerprints. By leveraging textural features and interpretable ML, it achieves robust classification of blood abnormalities with over 95% accuracy.
Anusuya Pal +2 more
wiley +1 more source
Bayesian Statistics for Beginners, 2019 This chapter focuses on Bayes’ Theorem. The chapter first gives a brief introduction to Thomas Bayes, who first formulated the theorem. It then builds on the content presented in Chapters 1 and 2 to derive Bayes’ Theorem and describes two ways to think ...
Therese M. Donovan, R. Mickey
semanticscholar +3 more sources
Advanced Physics Research, EarlyView.Cd2SnO4 exhibits excellent thermoelectric properties with a high Seebeck coefficient, power factor, and figure of merit, surpassing Bi2Te3. It shows both positive and negative Seebeck coefficient values, making it suitable for diverse applications. Its high electrical conductivity and low thermal conductivity enhance efficiency, while its negative Hall
Adel Bandar Alruqi, Nicholas O. Ongwen
wiley +1 more source
Network meta-analysis: application and practice using R software [PDF]
Epidemiology and Health, 2019 The objective of this study is to describe the general approaches to network meta-analysis that are available for quantitative data synthesis using R software.
Sung Ryul Shim +3 more
doaj +1 more source
Posterior probability and fluctuation theorem in stochastic processes
, 2009 A generalization of fluctuation theorems in stochastic processes is proposed. The new theorem is written in terms of posterior probabilities, which are introduced via the Bayes theorem.
Crooks G. E. +21 more
core +1 more source
Total Belief Theorem and Generalized Bayes' Theorem
Fusion, 2018 This paper presents two new theoretical contributions for reasoning under uncertainty: 1) the Total Belief Theorem (TBT) which is a direct generalization of the Total Probability Theorem, and 2) the Generalized Bayes' Theorem drawn from TBT.
J. Dezert, A. Tchamova, Deqiang Han
semanticscholar +1 more source
A Guide to Bayesian Optimization in Bioprocess Engineering
Biotechnology and Bioengineering, EarlyView.ABSTRACT Bayesian optimization has become widely popular across various experimental sciences due to its favorable attributes: it can handle noisy data, perform well with relatively small data sets, and provide adaptive suggestions for sequential experimentation.
Maximilian Siska +5 more
wiley +1 more source
Nonparametric empirical Bayes and compound decision approaches to estimation of a high-dimensional vector of normal means [PDF]
, 2009 We consider the classical problem of estimating a vector $\bolds{\mu}=(\mu_1,...,\mu_n)$ based on independent observations $Y_i\sim N(\mu_i,1)$, $i=1,...,n$. Suppose $\mu_i$, $i=1,...,n$ are independent realizations from a completely unknown $G$.
Brown, Lawrence D., Greenshtein, Eitan
core +3 more sources
Optimal model‐based design of experiments for parameter precision: Supercritical extraction case
The Canadian Journal of Chemical Engineering, EarlyView.Abstract This study investigates the process of chamomile oil extraction from flowers. A parameter‐distributed model consisting of a set of partial differential equations is used to describe the governing mass transfer phenomena in a cylindrical packed bed with solid chamomile particles under supercritical conditions using carbon dioxide as a solvent ...
Oliwer Sliczniuk, Pekka Oinas
wiley +1 more source