Biased sampling occurs frequently in economics, epidemiology, and medical studies either by design or due to data collecting mechanism. Failing to take into account the sampling bias usually leads to ...

Length-biased data analysis and survival modeling have become pivotal in accurately interpreting time-to-event data, particularly in epidemiology and clinical research. Traditional survival analyses ...

Although many authors have proposed different approaches to the analysis of length-biased survival data, a number of issues have not been fully addressed. The most important among these issues is ...

LONDON, Nov. 11 (UPI) --Most research looking at how and why people sample information focuses on "confirmation bias," the idea that people self-select information that confirms what they already ...

AI holds the potential to revolutionize healthcare, but it also brings with it a significant challenge: bias. For instance, a dermatologist might use an AI-driven system to help identify suspicious ...

Bias is an overloaded word. It has multiple meanings, from mathematics to sewing to machine learning, and as a result it’s easily misinterpreted. When people say an AI model is biased, they usually ...

Data collected by citizen science initiatives, museums and national parks is an important basis for research on biodiversity change. However, scientists found that sampling sites are oftentimes not ...

Machine learning provides a powerful way to automate decision making, but the algorithms don’t always get it right. When things go wrong, it’s often the machine learning model that gets the blame. But ...

An astonishing number of things that scientists know about brains and behavior are based on small groups of highly educated, mostly white people between the ages of 18 and 21. In other words, those ...