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 ...

Aim Although data collected by citizen scientists have received a great deal of attention for assessing species distributions over large extents, their sampling efforts are usually spatially biased.

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 in AI is pervasive. From dermatological models that discriminate against patients with darker skin to exam-scoring algorithms that disadvantage public school students, you don’t need to look far ...