Results 61 to 70 of about 26,331 (262)

TSTScope Unifies Single‐Cell Multi‐Omics to Identify Functional T Cell States Predictive of Immunotherapy Response

Advanced Science, EarlyView.
TSTScope is an interpretable AI framework that integrates single‐cell transcriptomes with TCR information through curated gene‐program constraints. By linking receptor context to functional T cell states, it reveals response‐associated tumor‐specific T cell programs in lung cancer immunotherapy cohorts and defines an MPR score associated with ...
Shiwei Cao, Jinyu Cheng, Feng‐ao Wang, Chenxin Yi, Jiajun Chen, Keyue Wang, Lulu Liu, Junwei Liu, Yixue Li   +8 more
wiley   +1 more source

Dopamine, affordance and active inference.

PLoS Computational Biology, 2012
The role of dopamine in behaviour and decision-making is often cast in terms of reinforcement learning and optimal decision theory. Here, we present an alternative view that frames the physiology of dopamine in terms of Bayes-optimal behaviour.
Karl J Friston, Tamara Shiner, Thomas FitzGerald, Joseph M Galea, Rick Adams, Harriet Brown, Raymond J Dolan, Rosalyn Moran, Klaas Enno Stephan, Sven Bestmann   +9 more
doaj   +1 more source

Pesticide MRLs as Trade Barriers: Evidence From Vietnam's Coffee and Rice Exporters

Agribusiness, EarlyView.
ABSTRACT As tariffs have declined globally through bilateral and regional trade agreements, food safety standards have emerged as significant determinants of agricultural trade flows. This study examines the impact of maximum residue limits (MRLs) for five pesticides—Azoxystrobin, Chlorpyrifos, Chlorantraniliprole, Clothianidin, and Cyhalothrin—on ...
Nhat Mai Nguyen, Hoa‐Thi‐Minh Nguyen, Kaliappa Kalirajan   +2 more
wiley   +1 more source

A conditional Bayesian approach for testing independence in two-way contingency tables

Kuwait Journal of Science, 2013
Bayesian methods for exact small-sample analysis with categorical data in   contingency tables are considered. Point null hypotheses versus two-sided hypothesis are tested concerning log odds ratios in these tables with fixed row margins. The conditional
Z. SABERI, M. GANJALI
doaj  

Advances in Thermal Modeling and Simulation of Lithium‐Ion Batteries with Machine Learning Approaches

Advanced Intelligent Discovery, EarlyView.
Heat generation in lithium‐ion batteries affects performance, aging, and safety, requiring accurate thermal modeling. Traditional methods face efficiency and adaptability challenges. This article reviews machine learning‐based and hybrid modeling approaches, integrating data and physics to improve parameter estimation and temperature prediction ...
Qi Lin, Kang Fu, Junjie Ding, Kai Sun, Peng Tan   +4 more
wiley   +1 more source

The Empirical Bayes Estimators of the Variance Parameter of the Normal Distribution with a Normal-Inverse-Gamma Prior Under Stein’s Loss Function

Axioms
For the hierarchical normal and normal-inverse-gamma model, we derive the Bayesian estimator of the variance parameter in the normal distribution under Stein’s loss function—a penalty function that treats gross overestimation and underestimation equally ...
Ying-Ying Zhang
doaj   +1 more source

A Cooperative Binary-Clustering Framework Based on Majority Voting for Twitter Sentiment Analysis

IEEE Access, 2020
Twitter sentiment analysis is a challenging problem in natural language processing. For this purpose, supervised learning techniques have mostly been employed, which require labeled data for training.
Maryum Bibi, Wajid Aziz, Majid Almaraashi, Imtiaz Hussain Khan, Malik Sajjad Ahmed Nadeem, Nazneen Habib   +5 more
doaj   +1 more source

On minimaxity and admissibility of hierarchical Bayes estimators

Journal of Multivariate Analysis, 2007
AbstractThis paper obtains conditions for minimaxity of hierarchical Bayes estimators in the estimation of a mean vector of a multivariate normal distribution. Hierarchical prior distributions with three types of second stage priors are treated. Conditions for admissibility and inadmissibility of the hierarchical Bayes estimators are also derived using
Kubokawa, Tatsuya, Strawderman, William E.   +1 more
openaire   +1 more source

Toward Predictable Nanomedicine: Current Forecasting Frameworks for Nanoparticle–Biology Interactions

Advanced Intelligent Discovery, EarlyView.
Predictive models successfully screen nanoparticles for toxicity and cellular uptake. Yet, complex biological dynamics and sparse, nonstandardized data limit their accuracy. The field urgently needs integrated artificial intelligence/machine learning, systems biology, and open‐access data protocols to bridge the gap between materials science and safe ...
Mariya L. Ivanova, Michael Nicholls, Nicola Russo, Gueorgui Mihaylov, Konstantin Nikolic   +4 more
wiley   +1 more source

Fully Bayesian Inference for Meta-Analytic Deconvolution Using Efron’s Log-Spline Prior

Mathematics
Meta-analytic deconvolution seeks to recover the distribution of true effects from noisy site-specific estimates. While Efron’s log-spline prior provides an elegant empirical Bayes solution with excellent point estimation properties, its plug-in nature ...
JoonHo Lee, Daihe Sui
doaj   +1 more source