Results 41 to 50 of about 840,461 (231)

Real‐world effectiveness and safety of secukinumab in giant cell arteritis: an Italian multicentre cohort study

Arthritis Care &Research, Accepted Article.
Objective The objective of this study was to evaluate the real‐world effectiveness and safety of secukinumab in giant cell arteritis (GCA) patients. Methods This multicentre retrospective study included patients with GCA who received secukinumab at 14 Italian centres with at least 6 months of follow‐up.
Luca Iorio, Federica Davanzo, Caterina Ricordi, Milena Bond, Ruggiero Mascolo, Jacopo Mora, Alessandro Tomelleri, Angelo Fassio, Francesca Cuzzocrea, Sara Monti, Edoardo Conticini, Fabiola Atzeni, Paolo Delvino, Carlotta Nannini, Augusta Ortolan, Francesco Pollastri, Ester Vivaldelli, Chiara Marvisi, Paola Toniati, Antonio Brucato, Alessandra Milanesi, Francesca Regola, Enrico Tombetti, Lorenzo Dagna, Roberta Ramonda, Christian Dejaco, Luca Quartuccio, Carlo Salvarani, Roberto Padoan, The Italian Society of Rheumatology Vasculitis Study Group   +29 more
wiley   +1 more source

Issues and Requirements for Bayesian Approaches in Context Aware Systems [PDF]

, 2005
Research in advanced context-aware systems has clearly shown a need to capture the inherent uncertainty in the physical world, especially in human behavior.
Strang, Thomas, Patrick Robertson, Robertson, Patrick, Michael Angermann, Angermann, Michael, Thomas Strang   +5 more
core   +1 more source

The Effect of Visualization on Students’ Understanding of Probability Concepts

Journal of Statistics and Data Science Education
Bayesian reasoning—the optimal process of updating a hypothesis or belief with new information—is a critical aspect of both everyday decision-making and statistics education, but strategies for effectively teaching the topic in the classroom remain ...
John M. Vargas, Jeffrey J. Starns, Andrew L. Cohen, Darrell Earnest   +3 more
doaj   +1 more source

dynoGP: Deep Gaussian Processes for Dynamic System Identification

International Journal of Adaptive Control and Signal Processing, EarlyView.
This work introduces a novel class of deep models for system identification, dynamical deep Gaussian processes, which combine the strengths of data‐driven methods, such as those based on neural network architectures, with the ability to output a probability distribution for uncertainty representation.
Alessio Benavoli, Marco Forgione, Dario Piga, Marco Zaffalon   +3 more
wiley   +1 more source

Challenges to Bayesian Confirmation Theory [PDF]

, 2011
While Bayesian analysis has enjoyed notable success with many particular problems of inductive inference, it is not the one true and universal logic of induction. I review why the Bayesian approach fails to provide this universal logic of induction. Some
Norton, JD, John D. Norton, Norton, John D.   +2 more
core   +1 more source

Image Recognition as a “Dialogic AI Partner” Within Biodiversity Citizen Science—an empirical investigation

Citizen Science: Theory and Practice
We investigate the potential of a new citizen science paradigm that facilitates collaborative learning between humans and artificial intelligence (AI).
Nirwan Sharma, Laura Colucci-Gray, Poppy Lakeman-Fraser, Annie Robinson, Julie Newman, René Van der Wal, Stefan Rueger, Advaith Siddharthan   +7 more
doaj   +1 more source

A Workflow to Accelerate Microstructure‐Sensitive Fatigue Life Predictions

Advanced Engineering Materials, EarlyView.
This study introduces a workflow to accelerate predictions of microstructure‐sensitive fatigue life. Results from frameworks with varying levels of simplification are benchmarked against published reference results. The analysis reveals a trade‐off between accuracy and model complexity, offering researchers a practical guide for selecting the optimal ...
Luca Loiodice, Krzysztof S. Stopka, Michael D. Sangid   +2 more
wiley   +1 more source

Machine Learning‐Supported Analysis for Predicting and Visualizing Nonlinear Relationships Between Material Properties in Electroplated Chromium Layers

Advanced Engineering Materials, EarlyView.
This study applies machine learning regression to predict chromium layer thickness in decorative trivalent chromium electroplating, using 441 experiments from laboratory‐scale (1L) and pilot‐scale (14L) setups. Tree‐based models, particularly CatBoost, outperformed linear regression by capturing nonlinear parameter interactions (R2$R^2$ up to 0.77 ...
Christoph Baumer, Christopher Mai, Luca Eisentraut, Andreas Bund, Ricardo Buettner   +4 more
wiley   +1 more source

Combatting bayesian criticism: a bayesian-inspired critical checklist for judicial reasoning

Quaestio Facti
This paper develops a Bayesian-inspired checklist of critical questions designed to support probabilistic reasoning in legal contexts. Building on Mackor’s (2026) proposal, rather than requiring formal Bayesian models or numerical probabilities, the ...
Leya Lisa Hampson
doaj   +1 more source

BayesNetBP: An R Package for Probabilistic Reasoning in Bayesian Networks

Journal of Statistical Software, 2020
The BayesNetBP package has been developed for probabilistic reasoning and visualization in Bayesian networks with nodes that are purely discrete, continuous or mixed (discrete and continuous).
Han Yu, Janhavi Moharil, Rachael Hageman Blair   +2 more
doaj   +1 more source