Results 151 to 160 of about 131,402 (244)
Diagnosing ectopic pregnancy using the bayes theorem and neural network: a validation of a retrospective cohort study. [PDF]
Maroni L, Silva PC, Kunst R, Savaris RF.
europepmc +1 more source
ABSTRACT The fiscal sustainability of healthcare systems is increasingly strained by aging populations with two competing hypotheses dominating the literature. The Red Herring Hypothesis suggests that healthcare expenditures are driven more by proximity to death than by chronological age, while the Steepening Hypothesis examines whether expenditures ...
Malene Kallestrup‐Lamb +2 more
wiley +1 more source
Correction to: A software tool for applying Bayes' theorem in medical diagnostics. [PDF]
Chatzimichail T, Hatjimihail AT.
europepmc +1 more source
Diffusional magnetic resonance imaging anonymizing with variational autoencoder
Abstract Anonymization is a crucial de‐identification technique that protects data privacy while ensuring its utility for model building. Current generative models such as generative adversarial networks and variational auto‐encoders (VAEs) have been applied to medical image anonymization but mainly focus on general image features, lacking specificity ...
Yunheng Shen +4 more
wiley +1 more source
A Probabilistic Greedy Attempt to Be Fair in Neural Team Recommendation
ABSTRACT Neural team recommendation has brought state‐of‐the‐art efficacy while enhancing efficiency at forming teams of experts whose success in completing complex tasks is almost surely guaranteed. However, they overlook fairness, that is, predicted teams are heavily biased toward popular and male experts, falling short of recommending female or ...
Hamed Loghmani +4 more
wiley +1 more source
Comment on van Gemert et al. Child Abuse, Misdiagnosed by an Expertise Center-Part II-Misuse of Bayes' Theorem. Children 2023, 10, 843. [PDF]
Onkenhout NH +5 more
europepmc +1 more source
Efficient Deconvolution in Populational Inverse Problems
ABSTRACT This work is focused on the inversion task of inferring the distribution over parameters of interest, leading to multiple sets of observations. The potential to solve such distributional inversion problems is driven by the increasing availability of data, but a major roadblock is blind deconvolution, arising when the observational noise ...
Arnaud Vadeboncoeur +2 more
wiley +1 more source
This article aims at exploring and validating the use of 3D physics‐based simulated ground motions as seismic input for the derivation of seismic fragility curves based on nonlinear dynamic numerical analyses. Fragility curves are computed for a set of pre‐code (i.e., designed only for vertical loads), reinforced concrete building types representative ...
Chiara Smerzini, Vincenzo Manfredi
wiley +1 more source
In‐and‐Out: Algorithmic Diffusion for Sampling Convex Bodies
ABSTRACT We present a new random walk for uniformly sampling high‐dimensional convex bodies. It achieves state‐of‐the‐art runtime complexity with stronger guarantees on the output than previously known, namely in Rényi divergence (which implies TV, 𝒲2, KL, χ2$$ {\chi}^2 $$).
Yunbum Kook +2 more
wiley +1 more source

