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.

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 ...

Ravishankar, Pavan, Qingyu Mo, Edward McFowland III, and Daniel B. Neill. "Provable Detection of Propagating Sampling Bias in Prediction Models." Proceedings of the AAAI Conference on Artificial ...

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 ...

In this special guest feature, Sinan Ozdemir, Director of Data Science at Directly, points out how algorithmic bias has been one of the most talked-about issues in AI for years, yet it remains one of ...

As marketing and communications specialists in the AI space, it’s our responsibility to select the right words when it comes to communicating about responsible AI. Our words shape discussions, which ...