Causal inference is important in medical research to help determine if treatments are beneficial and if natural exposures are harmful. In many settings, data collection makes causal inference ...

Statistical inference in linear models centres on estimating relationships between a response variable and one or more predictors under the assumption that these relationships can be expressed as a ...

In the 21st century, artificial intelligence (AI) has emerged as a valuable approach in data science and a growing influence in medical research, 4-6 with an accelerating pace of innovation. This ...

Big Data—broadly considered as datasets whose size, complexity, and heterogeneity preclude conventional approaches to storage and analysis—continues to generate interest across many scientific domains ...

Researchers have developed MRZ, a new Mendelian randomization method that robustly classifies genetic instruments to deliver ...

In a perspective published in Psychoradiology, researchers from Shanghai Jiao Tong University confronted causal inference in clinical neuroscience research and advocate for more clarity and ...

Eleanor has an undergraduate degree in zoology from the University of Reading and a master’s in wildlife documentary production from the University of Salford.View full profile Eleanor has an ...