AIMC Topic: Bias

Clear Filters Showing 301 to 310 of 330 articles

How Convolutional Neural Network Architecture Biases Learned Opponency and Color Tuning.

Neural computation
Recent work suggests that changing convolutional neural network (CNN) architecture by introducing a bottleneck in the second layer can yield changes in learned function. To understand this relationship fully requires a way of quantitatively comparing...

Bias at warp speed: how AI may contribute to the disparities gap in the time of COVID-19.

Journal of the American Medical Informatics Association : JAMIA
The COVID-19 pandemic is presenting a disproportionate impact on minorities in terms of infection rate, hospitalizations, and mortality. Many believe artificial intelligence (AI) is a solution to guide clinical decision-making for this novel disease,...

Latent bias and the implementation of artificial intelligence in medicine.

Journal of the American Medical Informatics Association : JAMIA
Increasing recognition of biases in artificial intelligence (AI) algorithms has motivated the quest to build fair models, free of biases. However, building fair models may be only half the challenge. A seemingly fair model could involve, directly or ...

Accurate deep-learning estimation of chlorophyll-a concentration from the spectral particulate beam-attenuation coefficient.

Optics express
Different techniques exist for determining chlorophyll-a concentration as a proxy of phytoplankton abundance. In this study, a novel method based on the spectral particulate beam-attenuation coefficient (c) was developed to estimate chlorophyll-a con...

Empirical assessment of bias in machine learning diagnostic test accuracy studies.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: Machine learning (ML) diagnostic tools have significant potential to improve health care. However, methodological pitfalls may affect diagnostic test accuracy studies used to appraise such tools. We aimed to evaluate the prevalence and rep...