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 ...

Scientific ideas sometimes have to wait decades for technology to catch up. Statistical algorithms developed at the Yerevan ...

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 ...

The advent of big data has transformed the landscape of statistical science, demanding methods that can handle unprecedented volume, velocity and variety. Traditional inference techniques, designed ...

All of the captive kea were given the opportunity to participate in the sampling task, but not all of them were interested. (Credit: Amalia Bastos.) Those remarkable kea are at it again: now the ...

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 ...

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