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 ...

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 ...

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 ...

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 ...

Artificial intelligence (AI) tools used in medicine, like AI used in other fields, work by detecting patterns in large volumes of data. AI tools are able to detect these patterns because they can ...

Your Artstor image groups were copied to Workspace. The Artstor website will be retired on Aug 1st. Diversity and Distributions Vol. 30, No. 6, June 2024 Causes and effects of sampling bias on m ...

Recently, an Association Workforce Monitor online survey conducted by the Harris Poll asked over 2,000 U.S. adults their thoughts on AI recruiting tools. About one-third of respondents in this recent ...

AI should be a dream for any chief data officer, but before you can embrace the full creative effectiveness and efficiencies of AI, there’s a problem afflicting its ability to produce strong ideas ...