Results 131 to 140 of about 77,058 (245)

EcoViz: a tool for visual analysis and photorealistic rendering of forest landscape model simulations

Ecography, EarlyView.
Simulation outputs from forest landscape models are complex, and tools for their visual analysis and effective communication are often limited. In this paper, we present EcoViz, a novel, open‐source visualisation platform designed to complement existing forest models by providing advanced 3D visualisation capabilities.
Werner Rammer, Eric Guérin, Patrick Marais, Adrien Peytavie, Konrad Kapp, Eric Galin, Rupert Seidl, James Gain   +7 more
wiley   +1 more source

Rare event detection by progressive clustering undersampling. [PDF]

PLoS One
Abuzeid A, Jolkver E.
europepmc   +1 more source

Machine Learning‐Assisted Design of BaTiO3‐Based Superparaelectric High‐Entropy Ceramics with Superior Energy Storage

ENERGY &ENVIRONMENTAL MATERIALS, EarlyView.
This study employed an adaptive iterative strategy combining machine learning algorithms, domain knowledge, experimental design, and experimental feedback to aim to precisely and quickly discover high‐entropy ceramics with excellent energy storage performance.
Haowen Liu, Xiaoyan Zhang, Zhiyuan Ma, Kailong Ma, Xiwei Qi   +4 more
wiley   +1 more source

Comparing effect latencies in the visual world paradigm: Monte Carlo simulations to assess resampling-based procedures. [PDF]

Behav Res Methods
Minor S.
europepmc   +1 more source

Importance Resampling

, 2020
Nicolas Chopin, Omiros Papaspiliopoulos
openaire   +1 more source

Video‐based diagnostics supported by artificial intelligence as an opportunity to address the epilepsy diagnostic gap: A narrative review

Epilepsia, EarlyView.
Abstract Despite advancements in epilepsy care, a substantial diagnostic gap persists, particularly in resource‐limited settings. This narrative review explores the potential of video‐based diagnostics augmented by artificial intelligence (AI) to address this gap by enabling earlier and more accessible seizure detection and classification.
Gadi Miron, Robert Terziev, Maximilian Schöls, John McLaren, Tobias Loddenkemper, Jörg Wellmer, Sigrid Mues, Christian Meisel   +7 more
wiley   +1 more source

Enhancing TSH-based congenital hypothyroidism screening using machine learning and resampling algorithms. [PDF]

BMC Med Inform Decis Mak
De Furia A, Branco P, Henderson M.
europepmc   +1 more source

Are seizure forecasts and cycles better than chance? What chance?

Epilepsia, EarlyView.
Abstract Objective There is a growing synergy between the lines of research on cycles in epilepsy and seizure forecasting. It has been conjectured, for instance, that incorporating information about significant seizure cycles into forecasting algorithms can lead to a better‐than‐chance forecasting performance.
Ralph G. Andrzejak, Martin Brešar, Mark P. Richardson, Pedro F. Viana, Richard Rosch   +4 more
wiley   +1 more source

Detection of rare medical events in electronic health records using machine learning: Current practices and suggestions - A scoping review. [PDF]

PLoS One
Gebeyehu B, Kleinberg B, Van Deun K, de Vries E.   +3 more
europepmc   +1 more source

A Multivariate Mixed‐Effects Regression Framework for Ground Motion Modeling: Integrating Parametric and Machine Learning Approaches

Earthquake Engineering &Structural Dynamics, EarlyView.
ABSTRACT Multivariate ground motion models (GMMs) that capture the correlation between different intensity measures (IMs) are essential for seismic risk assessment. Conventional GMMs are often developed using a two‐stage approach, where separate univariate models with predefined functional forms are fitted first, and correlation is addressed in a ...
Sayed Mohammad Sajad Hussaini, Shaghayegh Karimzadeh, Paulo B. Lourenço   +2 more
wiley   +1 more source