BACKGROUND: The first 90 days after dialysis initiation are associated with high morbidity and mortality in end-stage kidney disease (ESKD) patients. A machine learning-based tool for predicting mortality could inform patient-clinician shared decisio...
We present a general framework for causal mediation analysis using nonparametric Bayesian methods in the potential outcomes framework. Our model, which we refer to as the Bayesian causal mediation forests model, combines recent advances in Bayesian m...
Evaluation of the head shape of newborns is needed to detect cranial deformities, disturbances in head growth, and consequently, to predict short- and long-term neurodevelopment. Currently, there is a lack of automatic tools to provide a detailed eva...
International journal of health geographics
Jun 6, 2022
BACKGROUND: Local policymakers require information about public health, housing and well-being at small geographical areas. A municipality can for example use this information to organize targeted activities with the aim of improving the well-being o...
IEEE transactions on pattern analysis and machine intelligence
Jun 3, 2022
A sum-product network (SPN) is a probabilistic model, based on a rooted acyclic directed graph, in which terminal nodes represent probability distributions and non-terminal nodes represent convex sums (weighted averages) and products of probability d...
Arboviruses are a group of diseases that are transmitted by an arthropod vector. Since they are part of the Neglected Tropical Diseases that pose several public health challenges for countries around the world. The arboviruses' dynamics are governed ...
Computational intelligence and neuroscience
Jun 3, 2022
Transformer neural models with multihead attentions outperform all existing translation models. Nevertheless, some features of traditional statistical models, such as prior alignment between source and target words, prove useful in training the state...
Identifying a biomarker or treatment-dose threshold that marks a specified level of risk is an important problem, especially in clinical trials. In view of this goal, we consider a covariate-adjusted threshold-based interventional estimand, which hap...
Artificial neural networks inspired from the learning mechanism of the brain have achieved great successes in machine learning, especially those with deep layers. The commonly used neural networks follow the hierarchical multilayer architecture with ...
Analysis of longitudinal Electronic Health Record (EHR) data is an important goal for precision medicine. Difficulty in applying Machine Learning (ML) methods, either predictive or unsupervised, stems in part from the heterogeneity and irregular samp...