Results 181 to 190 of about 396,010 (290)

Near-End-of-Life Trajectory in Patients with Advanced Lung Cancer. [PDF]

Yonago Acta Med
Kinoshita N, Yamamoto M, Ikeuchi T, Touge H, Tomita K, Yamasaki A.   +5 more
europepmc   +1 more source

Bayesian Optimisation for the Experimental Sciences: A Practical Guide to Data‐Efficient Optimisation of Laboratory Workflows

Advanced Intelligent Systems, EarlyView.
This study provides an introduction to Bayesian optimisation targeted for experimentalists. It explains core concepts, surrogate modelling, and acquisition strategies, and addresses common real‐world challenges such as noise, constraints, mixed variables, scalability, and automation.
Chuan He, Martin Singull, T. Jesper Jacobsson   +2 more
wiley   +1 more source

Bayesian spatiotemporal evaluation of bovine anaplasmosis seroprevalence in Missouri (2010-2021). [PDF]

Front Vet Sci
Raghavan RK, Ierardi R, Osei FB, Zhang S.   +3 more
europepmc   +1 more source

Enabling Stochastic Dynamic Games for Robotic Swarms

Advanced Intelligent Systems, EarlyView.
This paper scales stochastic dynamic games to large swarms of robots through selective agent modeling and variable partial belief space planning. We formulate these games using a belief space variant of iterative Linear Quadratic Gaussian (iLQG). We scale to teams of 50 agents through selective modeling based on the estimated influence of agents ...
Kamran Vakil, Alyssa Pierson
wiley   +1 more source

Design and analysis of behavioral intervention studies: A Bayesian approach. [PDF]

PLoS One
Barragan Ibañez CN, Lösener U, Moeteke N, Moerbeek M.   +3 more
europepmc   +1 more source

Artificial Intelligence in Autonomous Mobile Robot Navigation: From Classical Approaches to Intelligent Adaptation

Advanced Intelligent Systems, EarlyView.
Artificial intelligence (AI) is reshaping autonomous mobile robot navigation beyond classical pipelines. This review analyzes how AI techniques are integrated into core navigation tasks, including path planning and control, localization and mapping, perception, and context‐aware decision‐making. Learning‐based, probabilistic, and soft‐computing methods
Giovanna Guaragnella, Angelo Cardellicchio, Cosimo Patruno, Massimiliano Nitti, Nicola Pedrocchi, Vito Renò   +5 more
wiley   +1 more source

Comparative performance of the patient-generated subjective global assessment, European Society for Clinical Nutrition and Metabolism criteria, and Global Leadership Initiative on Malnutrition criteria in patients with colorectal cancer: a multicenter study utilizing Bayesian inference. [PDF]

Front Nutr
Zhang ZC, Jin WD, Ma HJ, Zhang Y, Li Y, Zhu J, Qiao YH, Du YT, Jiang Y, Song JW, Wang JL, Liu S, Guo YJ, Kang BY, Wang Q, Qin SH, Song CH, Shi HP, Li JP.   +18 more
europepmc   +1 more source

To Raise or Not to Raise: An Experimental Test of Community Support for Increasing the Minimum Age of Criminal Responsibility in New South Wales, Australia

Australian Journal of Social Issues, EarlyView.
ABSTRACT While research has identified a disconnect between the minimum age of criminal responsibility (MACR) and public perceptions of criminal culpability among young people, no study has examined how offender characteristics influence support for reform using an experimental design. To address this, this study presents the first experimental test of
Cameron T. Langfield, Natalia Hanley, Jason L. Payne, Helen Simpson   +3 more
wiley   +1 more source

Optimal exercise prescription for depression and anxiety in children and adolescents: a Bayesian dose-response network meta-analysis protocol. [PDF]

Syst Rev
Zang W, Wu J, Liu N, Fang M, Xiao N, Wu J, Liu J, Zhang Q.   +7 more
europepmc   +1 more source

Individualized Atrophy‐Based Prediction of Dementia Progression in Familial Frontotemporal Lobar Degeneration With Bayesian Linear Mixed‐Effects Modeling

Annals of Neurology, EarlyView.
Objective Age of symptom onset is highly variable in familial frontotemporal lobar degeneration (f‐FTLD). Accurate prediction of onset would inform clinical management and trial enrollment. Prior studies indicate that individualized maps of brain atrophy can predict conversion to dementia in f‐FTLD.
Shubir Dutt, Dana Leichter, Yann Cobigo, Amy Wolf, John Kornak, Annie Clark, Lucy L. Russell, Arabella Bouzigues, David M. Cash, Martina Bocchetta, Molly Olzinski, Brian Appleby, Ece Bayram, Barbara Borroni, Andrea Bozoki, Chris R. Butler, David Clark, Rhian S. Convery, R. Ryan Darby, Alexandre de Mendonça, Bradford Dickerson, Kimiko Domoto‐Reilly, Simon Ducharme, Eve Ferry‐Bolder, Elizabeth Finger, Phoebe H. Foster, Douglas R. Galasko, Daniela Galimberti, Alexander Gerhard, Nupur Ghoshal, Caroline Graff, Neill Graff‐Radford, Ian M. Grant, Chadwick M. Hales, Lawrence S. Honig, Ging‐Yuek Hsiung, Edward D. Huey, David Irwin, Lize C. Jiskoot, Walter Kremers, Justin Y. Kwan, Robert Laforce, Isabelle Le Ber, Gabriel C. Léger, Johannes Levin, Irene Litvan, Ian R. Mackenzie, Mario Masellis, Mario F. Mendez, Fermin Moreno, Chiadi Onyike, Markus Otto, Belen Pascual, Peter Pressman, Rosa Rademakers, Eliana Marisa Ramos, Aaron Ritter, Erik D. Roberson, James B. Rowe, Raquel Sanchez‐Valle, Isabel Santana, Harro Seelaar, Allison Snyder, Sandro Sorbi, Matthis Synofzik, Maria Carmela Tartaglia, Pietro Tiraboschi, John C. van Swieten, Marijne Vandebergh, Rik Vandenberghe, Hilary W. Heuer, Bruce L. Miller, William W. Seeley, Maria Luisa Gorno‐Tempini, Joel H. Kramer, Leah Forsberg, Kejal Kantarci, Bradley F. Boeve, Adam L. Boxer, Jonathan D. Rohrer, Howard J. Rosen, Adam M. Staffaroni, FTD Prevention Initiative (FPI) investigators   +82 more
wiley   +1 more source