Zobrazeno 1 - 10
of 215
pro vyhledávání: '"Scutari, Marco"'
Publikováno v:
Scientific Reports (2024), 14, 10266
The relationship between skin diseases and mental illnesses has been extensively studied using cross-sectional epidemiological data. Typically, such data can only measure association (rather than causation) and include only a subset of the diseases w
Externí odkaz:
http://arxiv.org/abs/2405.06405
Autor:
Scutari, Marco
Publikováno v:
Algorithms (2024), 17(1), 24
Bayesian networks (BNs) are a foundational model in machine learning and causal inference. Their graphical structure can handle high-dimensional problems, divide them into a sparse collection of smaller ones, underlies Judea Pearl's causality, and de
Externí odkaz:
http://arxiv.org/abs/2312.01520
Over the last decades, many prognostic models based on artificial intelligence techniques have been used to provide detailed predictions in healthcare. Unfortunately, the real-world observational data used to train and validate these models are almos
Externí odkaz:
http://arxiv.org/abs/2311.08427
Publikováno v:
Proceedings of the 30th International Symposium on Temporal Representation and Reasoning (TIME 2023), Leibniz International Proceedings in Informatics (LIPIcs), 8:1-8:21
Interacting systems of events may exhibit cascading behavior where events tend to be temporally clustered. While the cascades themselves may be obvious from the data, it is important to understand which states of the system trigger them. For this pur
Externí odkaz:
http://arxiv.org/abs/2308.10606
Publikováno v:
Engineering Applications of Artificial Intelligence (2024), 31, 107867
Maize, a crucial crop globally cultivated across vast regions, especially in sub-Saharan Africa, Asia, and Latin America, occupies 197 million hectares as of 2021. Various statistical and machine learning models, including mixed-effect models, random
Externí odkaz:
http://arxiv.org/abs/2308.06399
Autor:
Zanga, Alessio, Bernasconi, Alice, Lucas, Peter J. F., Pijnenborg, Hanny, Reijnen, Casper, Scutari, Marco, Stella, Fabio
Causal inference for testing clinical hypotheses from observational data presents many difficulties because the underlying data-generating model and the associated causal graph are not usually available. Furthermore, observational data may contain mi
Externí odkaz:
http://arxiv.org/abs/2305.10050
Autor:
Zanga, Alessio, Bernasconi, Alice, Lucas, Peter J. F., Pijnenborg, Hanny, Reijnen, Casper, Scutari, Marco, Stella, Fabio
Assessing the pre-operative risk of lymph node metastases in endometrial cancer patients is a complex and challenging task. In principle, machine learning and deep learning models are flexible and expressive enough to capture the dynamics of clinical
Externí odkaz:
http://arxiv.org/abs/2305.10041
Autor:
Scutari, Marco
The adoption of machine learning in applications where it is crucial to ensure fairness and accountability has led to a large number of model proposals in the literature, largely formulated as optimisation problems with constraints reducing or elimin
Externí odkaz:
http://arxiv.org/abs/2305.02009