… Second, the role of data for AF becomes inevitable, such that Chatterjee et al.'s (2021)
attempt to include information as a component seemed beneficial for our purposes. We claim the …

… 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction
in any medium or format, as long as you give appropriate credit to the original author(s) …

… a true S. aureus sample (0/492, upper 97.5% confidence interval 0.7%). We studied the
three non-S. aureus samples that appeared to be misclassified by Mykrobe predictor as S. …

… S 0 =zero mutations present. S B =only benign mutations present. U=uncharacterised
mutations present in the absence of a resistance-determining mutation. Characterised mutations …

Several sources of bias can affect the performance of machine learning systems used in
medicine and potentially impact clinical care. Here, we discuss solutions to mitigate bias across …

… During the first round, two authors (AL and NB) extracted data from an initial set of 20
publications, blinded to each other’s coding. The coding was then compared, and any differences …

Antibiotic-resistant tuberculosis poses a global threat, causing the deaths of hundreds of
thousands of people annually. While whole-genome sequencing (WGS), with its unprecedented …

… T based on a different, yet related, source task S with dataset D S . After optimizing the
parameters of our network for S on D S we replace the task-specific prediction layer of the network …

… = 1 m p i k Y ij k + p j k + s ij k X ij k + Y ij k ∑ l = 0 n X li k s li k (C1) s . t . ∑ i = 0 n ∑ k = 1 m
… time s 0 j k ⩾ 0 to move from its starting location to incident j. In addition to that, we set s j ( n …

… network parameterized by θ, while s i is the hidden state and h i … state s i and the current input
x i +1 , ie (1) h i + 1 = A θ s i , x i + 1 . … onwards from the current state s i to the next s i +1 . To …