Results 141 to 150 of about 91,736 (294)
Threshold‐optimized machine learning models using routine clinical and laboratory data in 623 adults undergoing appendectomy. Logistic regression (AUC = 0.765) and random forest (AUC = 0.785) were the best‐performing models for appendicitis detection and complicated appendicitis prediction, respectively.
Ivan Males +8 more
wiley +1 more source
Hierarchical Reasoning versus Iterated Reasoning in p-Beauty Contest Guessing Games
This paper analyzes strategic choice in p-beauty contests. We first show that it is not generally a best reply to guess the expected target value (accounting for the own weight) even in games with n>2 players and that iterated best response sequences are
Breitmoser, Yves
core +1 more source
CrossMatAgent is a multi‐agent framework that combines large language models and diffusion‐based generative AI to automate metamaterial design. By coordinating task‐specific agents—such as describer, architect, and builder—it transforms user‐provided image prompts into high‐fidelity, printable lattice patterns.
Jie Tian +12 more
wiley +1 more source
Deep Learning‐Assisted Coherent Raman Scattering Microscopy
The analytical capabilities of coherent Raman scattering microscopy are augmented through deep learning integration. This synergistic paradigm improves fundamental performance via denoising, deconvolution, and hyperspectral unmixing. Concurrently, it enhances downstream image analysis including subcellular localization, virtual staining, and clinical ...
Jianlin Liu +4 more
wiley +1 more source
Topology‐Aware Machine Learning for High‐Throughput Screening of MOFs in C8 Aromatic Separation
We screened 15,335 Computation‐Ready, Experimental Metal–Organic Frameworks (CoRE‐MOFs) using a topology‐aware machine learning (ML) model that integrates structural, chemical, pore‐size, and topological descriptors. Top‐performing MOFs exhibit aromatic‐enriched cavities and open metal sites that enable π–π and C–H···π interactions, serving as ...
Yu Li, Honglin Li, Jialu Li, Wan‐Lu Li
wiley +1 more source
On the J-test for nonnested hypotheses and Bayesian extension
Davidson and MacKinnon’s J-test was developed to test non-nested model specification. In empirical applications, however, when the alternate specifications fit the data well the J test may fail to distinguish between the true and false models: the J test
Krieg, John, Rao, Surekha, Ghali, Moheb
core +1 more source
This article implements a unified human digital twin framework that integrates cutting edge actuation, sensing, simulation, and bidirectional feedback capability. The approach includes integrating multimodal sensing, AI, and biomechanical simulation into one compact system.
Tajbeed Ahmed Chowdhury +4 more
wiley +1 more source
The Interoperability Challenge in DFT Workflows Across Implementations
Interoperability and cross‐validation remain major challenges in the computational materials science. In this work, we introduce a common input/output standard that enables internal translation across multiple workflow managers—AiiDA, PerQueue, Pipeline Pilot, and SimStack—while producing results in a unified schema.
Simon K. Steensen +13 more
wiley +1 more source
Estimation with the Nested Logit Model: Specifications and Software Particularities [PDF]
Due to its ability to allow and account for similarities betweenpairs of alternatives, the nested logit model is increasingly used in practical applications.
Nadja Silberhorn +2 more
core
The Impact of Heavy-tailed Error Distributions on Partially Nested Randomized Controlled Trials Models [PDF]
University of Minnesota Ph.D. dissertation. September 2017. Major: Educational Psychology. Advisor: Michael Harrell. 1 computer file (PDF); x, 197 pages.The Partially Nested Randomized Control Trial (PNRCT) model can be used when the subjects within the ...
Moreno, Mario
core

