Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Learning Hierarchical Attention for Weakly-supervised Chest X-Ray
  Abnormality Localization and Diagnosis   We consider the problem of abnormality localization for clinical
applications. While deep learning has driven much recent progress in medical
imaging, many clinical challenges are not fully addressed, limiting its broader
usage. While recent methods report high diagnostic accuracies, physicians have
concerns trusting these algorithm results for diagnostic decision-making
purposes because of a general lack of algorithm decision reasoning and
interpretability. One potential way to address this problem is to further train
these models to localize abnormalities in addition to just classifying them.
However, doing this accurately will require a large amount of disease
localization annotations by clinical experts, a task that is prohibitively
expensive to accomplish for most applications. In this work, we take a step
towards addressing these issues by means of a new attention-driven weakly
supervised algorithm comprising a hierarchical attention mining framework that
unifies activation- and gradient-based visual attention in a holistic manner.
Our key algorithmic innovations include the design of explicit ordinal
attention constraints, enabling principled model training in a
weakly-supervised fashion, while also facilitating the generation of
visual-attention-driven model explanations by means of localization cues. On
two large-scale chest X-ray datasets (NIH ChestX-ray14 and CheXpert), we
demonstrate significant localization performance improvements over the current
state of the art while also achieving competitive classification performance.
Our code is available on https://github.com/oyxhust/HAM.

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The categories of this paper are: cond-mat
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The categories of this paper are: stat
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The categories of this paper are: mtrl-th
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The categories of this paper are: adap-org
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The categories of this paper are: hep-ex
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The categories of this paper are: q-fin
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The categories of this paper are: astro-ph
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The categories of this paper are: funct-an
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The categories of this paper are: gr-qc
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The categories of this paper are: hep-th
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The categories of this paper are: hep-lat
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The categories of this paper are: supr-con
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The categories of this paper are: math
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The categories of this paper are: hep-ph
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The categories of this paper are: comp-gas
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The categories of this paper are: q-bio