Results 101 to 110 of about 8,838,426 (323)
A causal artificial intelligence model for payment delay optimisation in supply chain financing
Supply Chain AnalyticsSupply chain financing (SCF) has become a popular approach for small- and medium-sized enterprises (SMEs) to improve financial resilience. Payment delays within SCF have emerged as a critical operational challenge for both suppliers and SCF providers ...
Lingxuan Kong, Alexandra Brintrup
doaj +1 more source
Quantitative causality, causality-guided scientific discovery, and causal machine learning
CoRR10 pages, 3 figures. To appear in Ocean-Land-Atmosphere Research.
X. San Liang, Dake Chen, Renhe Zhang
openaire +2 more sources
Annals of Clinical and Translational Neurology, EarlyView.ABSTRACT Objectives Focal cortical dysplasia (FCD) is the most common etiology of drug‐resistant epilepsy in children. Focal to bilateral tonic–clonic seizures (FBTCS) mark a high risk of drug‐resistant epilepsy and involve thalamocortical circuitry in their generation and propagation.
Hua Xie +8 more
wiley +1 more source
Network for Statistical and Causal Inference, Pisa, 11 September
The ReasonerThis article reports the main content of the talks presented at the fourth meeting of the Network for Statistical and Causal Inference, at Sant'Anna School of Advanced Studies, Pisa, 11 September 2025.
Lorenzo Casini
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Predictive Value of Composite Inflammatory Markers for Stroke Prognosis: A Prospective Cohort Study
Annals of Clinical and Translational Neurology, EarlyView.ABSTRACT Background Novel composite inflammatory markers' role in stroke prognosis is understudied, and the best predictor is unclear, requiring further exploration. Objectives This study aimed to systematically evaluate the associations of 6 novel composite inflammatory markers on stroke prognosis.
Bing Wu +7 more
wiley +1 more source
Casual and trustworthy machine learning: methods and applications [PDF]
This work focuses on the intersection of machine learning and causal inference and the way in which the two fields can enhance each other by sharing ideas: utilizing machine learning techniques for the computation of causal quantities, the use of ideas ...
Gultchin, Limor
core +1 more source
Annals of Clinical and Translational Neurology, EarlyView.ABSTRACT Objective Autoimmune glial fibrillary acidic protein astrocytopathy (GFAP‐A) is an inflammatory central nervous system disorder with variable outcomes. Relapse occurs in a subset of patients, but early predictors remain unclear. We aimed to identify admission‐available features associated with 1‐year recurrence and develop an interpretable ...
Qingting Hong +10 more
wiley +1 more source
MACHINE LEARNING AND ECONOMETRICS: BRIDGING THE GAP FOR ENHANCED ECONOMIC ANALYSIS
مجلة الغري للعلوم الاقتصادية والاداريةThis paper explores the integration of machine learning techniques in econometric analysis, emphasizing the transformative impact on economic research.
Jamiu Adeniyi Yusuf +2 more
doaj +1 more source
Anticoagulation Treatment Response Among Phenotypic ESUS Clusters: Evidence From CASPR
Annals of Clinical and Translational Neurology, EarlyView.ABSTRACT Objective To evaluate treatment effect heterogeneity across phenotypic clusters of patients with cryptogenic embolic stroke using causal inference methods. Methods From a retrospective, multicenter cohort of patients with cryptogenic embolic stroke, we estimated the treatment effect of anticoagulation versus antiplatelet therapy in patients ...
Elena Badillo Goicoechea +53 more
wiley +1 more source
Space‐Time Causal Discovery in Earth System Science: A Local Stencil Learning Approach
Journal of Geophysical Research: Machine Learning and ComputationCausal discovery tools enable scientists to infer meaningful relationships from observational data, spurring advances in fields as diverse as biology, economics, and climate science.
J. Jake Nichol +5 more
doaj +1 more source