Results 111 to 120 of about 47,050 (138)

Causal Effects of Lifestyle and Dietary Factors on Rheumatoid Arthritis: An Integrated Analysis Combining Mendelian Randomization, Machine Learning, and Evaluation of Burden Dynamics and Health Inequality. [PDF]

Food Sci Nutr
Gao Y, Gu G, Wang R, Han W, Zheng B, Yang A, Wang N, Yu H, Jia C, Wang Y.   +9 more
europepmc   +1 more source

Integrating causal inference and machine learning to quantify climate-malaria relationships: Evidence of temperature and rainfall thresholds from Colombian municipalities. [PDF]

PLOS Glob Public Health
Gutiérrez JD.
europepmc   +1 more source

Multidimensional analysis and predictive modeling of cognitive decline risk in the United States using propensity score matching and machine learning. [PDF]

Medicine (Baltimore)
Li J, Chen G, Liu Y.
europepmc   +1 more source

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Causal Inference Meets Machine Learning

Proceedings of the 26th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2020
Causal inference has numerous real-world applications in many domains such as health care, marketing, political science and online advertising. Treatment effect estimation, a fundamental problem in causal inference, has been extensively studied in statistics for decades. However, traditional treatment effect estimation methods may not well handle large-
Peng Cui, Zheyan Shen, Sheng Li, Liuyi Yao, Yaliang Li, Zhixuan Chu, Jing Gao   +6 more
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Machine Learning, Health Disparities, and Causal Reasoning

Annals of Internal Medicine, 2018
Rajkomar and colleagues warn us that the introduction of machine-learned predictive algorithms into medicine might inadvertently reinforce or create inequitable treatment of protected groups, for w...
Steven N, Goodman, Sharad, Goel, Mark R, Cullen   +2 more
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Causal scientific explanations from machine learning

Synthese, 2023
Machine learning is used more and more in scientific contexts, from the recent breakthroughs with AlphaFold2 in protein fold prediction to the use of ML in parametrization for large climate/astronomy models. Yet it is unclear whether we can obtain scientific explanations from such models.
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Causal Machine Learning for Medical Texts

Text analysis has become increasingly common in medical research, especially for tasks like patient diagnosis based on medical notes. However, most existing approaches do not account for causal rela tionships between words and diagnoses. This paper proposes a causal approach using the MIMIC-III dataset to identify words or word pairs that causally ...
Alessandro Albano, Chiara Di Maria, Mariangela Sciandra, Antonella Plaia   +3 more
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