Results 91 to 100 of about 1,606,312 (290)

Spatial and Volumetric Characteristics of Glioblastoma: Associations With Clinical Presentation and Survival

open access: yesAnnals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective We aim to comprehensively analyze how regional tumor and edema characteristics are associated with clinical presentations and survival outcomes in a large cohort of glioblastoma patients. Methods Patients with IDH‐wildtype glioblastoma who received brain MRI from 2010 to 2023 were included.
Daniel J. Zhou   +15 more
wiley   +1 more source

Detecting and removing noisy instances from concept descriptions [PDF]

open access: yes, 1988
Several published results show that instance-based learning algorithms record high classification accuracies and low storage requirements when applied to supervised learning tasks.
Aha, David W., Kibler, Dennis
core  

Artificial Intelligence in Systemic Sclerosis: Clinical Applications, Challenges, and Future Directions

open access: yesArthritis Care &Research, EarlyView.
Systemic sclerosis (SSc) is a rare autoimmune disease defined by immune dysregulation, vasculopathy, and progressive fibrosis of the skin and internal organs. Despite advances in care, major complications such as interstitial lung disease (ILD) and myocardial involvement remain the leading causes of morbidity and mortality.
Cristiana Sieiro Santos   +2 more
wiley   +1 more source

A Q‐Learning Algorithm to Solve the Two‐Player Zero‐Sum Game Problem for Nonlinear Systems

open access: yesInternational Journal of Adaptive Control and Signal Processing, Volume 39, Issue 3, Page 566-581, March 2025.
A Q‐learning algorithm to solve the two‐player zero‐sum game problem for nonlinear systems. ABSTRACT This paper deals with the two‐player zero‐sum game problem, which is a bounded L2$$ {L}_2 $$‐gain robust control problem. Finding an analytical solution to the complex Hamilton‐Jacobi‐Issacs (HJI) equation is a challenging task.
Afreen Islam   +2 more
wiley   +1 more source

Causal Discovery in Astrophysics: Unraveling Supermassive Black Hole and Galaxy Coevolution

open access: yesThe Astrophysical Journal
Correlation does not imply causation, but patterns of statistical association between variables can be exploited to infer a causal structure (even with purely observational data) with the burgeoning field of causal discovery.
Zehao Jin   +11 more
doaj   +1 more source

Risk preferences of learning algorithms

open access: yesGames and Economic Behavior
Agents' learning from feedback shapes economic outcomes, and many economic decision-makers today employ learning algorithms to make consequential choices. This note shows that a widely used learning algorithm, $\varepsilon$-Greedy, exhibits emergent risk aversion: it prefers actions with lower variance.
Andreas A. Haupt, Aroon Narayanan
openaire   +3 more sources

A Robust Adaptive One‐Sample‐Ahead Preview Super‐Twisting Sliding Mode Controller

open access: yesInternational Journal of Adaptive Control and Signal Processing, EarlyView.
Block Diagram of the Robust Adaptive One‐Sample‐Ahead Preview Super‐Twisting Sliding Mode Controller. ABSTRACT This article introduces a discrete‐time robust adaptive one‐sample‐ahead preview super‐twisting sliding mode controller. A stability analysis of the controller by Lyapunov criteria is developed to demonstrate its robustness in handling both ...
Guilherme Vieira Hollweg   +5 more
wiley   +1 more source

Atari games and Intel processors

open access: yes, 2017
The asynchronous nature of the state-of-the-art reinforcement learning algorithms such as the Asynchronous Advantage Actor-Critic algorithm, makes them exceptionally suitable for CPU computations.
Adamski, Robert   +3 more
core   +1 more source

Characterization of Defect Distribution in an Additively Manufactured AlSi10Mg as a Function of Processing Parameters and Correlations with Extreme Value Statistics

open access: yesAdvanced Engineering Materials, EarlyView.
Predicting extreme defects in additive manufacturing remains a key challenge limiting its structural reliability. This study proposes a statistical framework that integrates Extreme Value Theory with advanced process indicators to explore defect–process relationships and improve the estimation of critical defect sizes. The approach provides a basis for
Muhammad Muteeb Butt   +8 more
wiley   +1 more source

A Novel Median Dendritic Neuron Model for Prediction

open access: yesIEEE Access, 2020
Dendritic neuron model (DNM) that utilizes a single dendritic neuron to emulate the information processing in human brains has been successfully applied to classification, approximation, and prediction fields.
Shi Wang   +6 more
doaj   +1 more source

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