AIMC Topic: Causality
Clear Filters Showing 51 to 60 of 106 articles
Causality matters in medical imaging.
Nature communications
Jul 22, 2020
Causal reasoning can shed new light on the major challenges in machine learning for medical imaging: scarcity of high-quality annotated data and mismatch between the development dataset and the target environment. A causal perspective on these issues...
Efficacy of intelligent diagnosis with a dynamic uncertain causality graph model for rare disorders of sex development.
Frontiers of medicine
Jul 17, 2020
Disorders of sex development (DSD) are a group of rare complex clinical syndromes with multiple etiologies. Distinguishing the various causes of DSD is quite difficult in clinical practice, even for senior general physicians because of the similar an...
Development of an artificial intelligence diagnostic model based on dynamic uncertain causality graph for the differential diagnosis of dyspnea.
Frontiers of medicine
Jul 16, 2020
Dyspnea is one of the most common manifestations of patients with pulmonary disease, myocardial dysfunction, and neuromuscular disorder, among other conditions. Identifying the causes of dyspnea in clinical practice, especially for the general practi...
A Method to Extract Causality for Safety Events in Chemical Accidents from Fault Trees and Accident Reports.
Computational intelligence and neuroscience
Jun 19, 2020
Chemical event evolutionary graph (CEEG) is an effective tool to perform safety analysis, early warning, and emergency disposal for chemical accidents. However, it is a complicated work to find causality among events in a CEEG. This paper presents a ...
Kernel Granger Causality Based on Back Propagation Neural Network Fuzzy Inference System on fMRI Data.
IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Mar 31, 2020
Granger causality (GC) is one of the most popular measures to investigate causality influence among brain regions and has been achieved significant results for exploring brain networks based on functional magnetic resonance imaging (fMRI). However, t...
Sensitivity Analysis and Extensions of Testing the Causal Direction of Dependence: A Rejoinder to Thoemmes (2019).
Multivariate behavioral research
Sep 23, 2019
A commentary by Thoemmes on Wiedermann and Sebastian's introductory article on Direction Dependence Analysis (DDA) is responded to in the interest of elaborating and extending direction dependence principles to evaluate causal effect directionality. ...
Extracting health-related causality from twitter messages using natural language processing.
BMC medical informatics and decision making
Apr 4, 2019
BACKGROUND: Twitter messages (tweets) contain various types of topics in our daily life, which include health-related topics. Analysis of health-related tweets would help us understand health conditions and concerns encountered in our daily lives. In...
Estimating Multiscale Direct Causality Graphs in Neural Spike-Field Networks.
IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Mar 28, 2019
Neural representations span various spatiotemporal scales of brain activity, from the spiking activity of single neurons to field activity measuring large-scale networks. The simultaneous analyses of spikes and fields to uncover causal interactions i...
Using Unlabeled Data to Discover Bivariate Causality with Deep Restricted Boltzmann Machines.
IEEE/ACM transactions on computational biology and bioinformatics
Nov 5, 2018
An important question in microbiology is whether treatment causes changes in gut flora, and whether it also affects metabolism. The reconstruction of causal relations purely from non-temporal observational data is challenging. We address the problem ...
Lost in translation.
F1000Research
May 21, 2018
Translation in cognitive neuroscience remains beyond the horizon, brought no closer by supposed major advances in our understanding of the brain. Unless our explanatory models descend to the individual level-a cardinal requirement for any interventio...
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