[HTML][HTML] Application of uncertainty quantification to artificial intelligence in healthcare: A review of last decade (2013–2023)
Uncertainty estimation in healthcare involves quantifying and understanding the inherent
uncertainty or variability associated with medical predictions, diagnoses, and treatment …
uncertainty or variability associated with medical predictions, diagnoses, and treatment …
[HTML][HTML] Trustworthy clinical AI solutions: a unified review of uncertainty quantification in deep learning models for medical image analysis
The full acceptance of Deep Learning (DL) models in the clinical field is rather low with
respect to the quantity of high-performing solutions reported in the literature. End users are …
respect to the quantity of high-performing solutions reported in the literature. End users are …
[HTML][HTML] Uncertainty estimation in medical image classification: systematic review
A Kurz, K Hauser, HA Mehrtens… - JMIR Medical …, 2022 - medinform.jmir.org
Background: Deep neural networks are showing impressive results in different medical
image classification tasks. However, for real-world applications, there is a need to estimate …
image classification tasks. However, for real-world applications, there is a need to estimate …
Should ensemble members be calibrated?
Underlying the use of statistical approaches for a wide range of applications is the
assumption that the probabilities obtained from a statistical model are representative of the" …
assumption that the probabilities obtained from a statistical model are representative of the" …