Open Heart

Artificial intelligence-based clustering to identify functional risk phenotypes in heart failure

Background Patients with heart failure (HF) frequently suffer from undetected declines in cardiorespiratory fitness (CRF), which significantly increases their risk of poor outcomes. However, current ...
Frontiers

A deep-learning approach to predict reproductive toxicity of chemicals using communicative message passing neural network

Reproductive toxicity is a concern critical to human health and chemical safety assessment. Recently, the U.S. Food and Drug Administration announced plans to assess toxicity with artificial ...
Frontiers

Machine learning approach for personalized vancomycin steady-state trough concentration prediction: a superior approach over Bayesian population pharmacokinetic model

Appropriate vancomycin trough levels are crucial for ensuring therapeutic efficacy while minimizing toxicity. The aim of this study is to identify clinical factors that influence the steady-state ...
Scientific Research Publishing

Comparing Classification Models for Predicting Malaria: A Case Study of Malaria Incidence in Kenya ()

1 Department of Mathematics, Meru University of Science & Technology (MUST), Meru, Kenya. 2 Department of Mathematics, Pan African University Institute of Basic Sciences Technology and Innovations ...
C&EN

Natural Gas Purification Plants Based on Interpretive Structural Models and Bayesian Networks

Article subjects are automatically applied from the ACS Subject Taxonomy and describe the scientific concepts and themes of the article. Natural gas purification plants are a critical part of the gas ...
www.cs.cmu.edu

Classical generalization theory is more predictive in foundation models than in conventional deep networks

Key takeaway: When learning over discrete prompts used in modern vision-language models, classical PAC-Bayes bounds turn out to be remarkably tight — significantly tighter than prior PAC-Bayes results ...
Scientific Research Publishing

Hahn, P.R., Murray, J.S. and Carvalho, C.M. (2020) Bayesian Regression Tree Models for Causal Inference: Regularization, Confounding, and Heterogeneous Effects (with Discussion ...

ABSTRACT: This study explores the application of Bayesian econometrics in policy evaluation through theoretical analysis. The research first reviews the theoretical foundations of Bayesian methods, ...
GitHub

bayesian-classifier

This repositories contains implementation of various Machine Learning Algorithms such as Bayesian Classifier, Principal Component Analysis, Fisher Linear Discriminator, Face Recognition and ...