Applying causal discovery to single-cell analyses using CausalCell [PDF]
eLife, 2023 Correlation between objects is prone to occur coincidentally, and exploring correlation or association in most situations does not answer scientific questions rich in causality.
Yujian Wen +7 more
doaj +2 more sources
Review of Causal Discovery Methods Based on Graphical Models
Frontiers in Genetics, 2019 A fundamental task in various disciplines of science, including biology, is to find underlying causal relations and make use of them. Causal relations can be seen if interventions are properly applied; however, in many cases they are difficult or even ...
Clark Glymour, Kun Zhang, Peter Spirtes
doaj +2 more sources
Diabetes Prediction Through Linkage of Causal Discovery and Inference Model with Machine Learning Models [PDF]
BiomedicinesBackground/Objectives: Diabetes is a dangerous disease that is accompanied by various complications, including cardiovascular disease. As the global diabetes population continues to increase, it is crucial to identify its causes.
Mi Jin Noh, Yang Sok Kim
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A guide to bayesian networks software for structure and parameter learning, with a focus on causal discovery tools [PDF]
Frontiers in Systems BiologyA representation of the cause-effect mechanism is needed to enable artificial intelligence to represent how the world works. Bayesian Networks (BNs) have proven to be an effective and versatile tool for this task.
Francesco Canonaco +5 more
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Can algorithms replace expert knowledge for causal inference? A case study on novice use of causal discovery. [PDF]
Am J EpidemiolWith growing interest in causal inference and machine learning among epidemiologists, there is increasing discussion of causal discovery algorithms for guiding covariate selection.
Gururaghavendran R, Murray EJ.
europepmc +2 more sources
AnchorFCI: harnessing genetic anchors for enhanced causal discovery of cardiometabolic disease pathways [PDF]
Frontiers in GeneticsIntroductionCardiometabolic diseases, a major global health concern, stem from complex interactions of lifestyle, genetics, and biochemical markers. While extensive research has revealed strong associations between various risk factors and these diseases,
Adèle H. Ribeiro +7 more
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Mental health progress requires causal diagnostic nosology and scalable causal discovery [PDF]
Frontiers in Psychiatry, 2022 Nine hundred and seventy million individuals across the globe are estimated to carry the burden of a mental disorder. Limited progress has been achieved in alleviating this burden over decades of effort, compared to progress achieved for many other ...
Glenn N. Saxe +4 more
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Correction: A guide to bayesian networks software for structure and parameter learning, with a focus on causal discovery tools [PDF]
Frontiers in Systems BiologyFrancesco Canonaco +5 more
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Collective Causal Relations Discovery Algorithm for Multivariate Time-Series [PDF]
Jisuanji gongcheng, 2023 Causal discovery from multivariate time-series is a significant and fundamental problem in numerous disciplines.The existing multivariate time-series causal discovery methods learn the causal relations for each individual while some individuals may share
CAI Ruichu, WU Yunjin, CHEN Wei, HAO Zhifeng
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Score matching enables causal discovery of nonlinear additive noise models [PDF]
International Conference on Machine Learning, 2022 This paper demonstrates how to recover causal graphs from the score of the data distribution in non-linear additive (Gaussian) noise models. Using score matching algorithms as a building block, we show how to design a new generation of scalable causal ...
Paul Rolland +6 more
semanticscholar +1 more source