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EGFR Mutation Prediction of Lung Biopsy Images using Deep Learning. (arXiv:2208.12506v1 [cs.CV])
Aug. 29, 2022, 1:14 a.m. | Ravi Kant Gupta, Shivani Nandgaonkar, Nikhil Cherian Kurian, Swapnil Rane, Amit Sethi
cs.CV updates on arXiv.org arxiv.org
The standard diagnostic procedures for targeted therapies in lung cancer
treatment involve histological subtyping and subsequent detection of key driver
mutations, such as EGFR. Even though molecular profiling can uncover the driver
mutation, the process is often expensive and time-consuming. Deep
learning-oriented image analysis offers a more economical alternative for
discovering driver mutations directly from whole slide images (WSIs). In this
work, we used customized deep learning pipelines with weak supervision to
identify the morphological correlates of EGFR mutation from …
More from arxiv.org / cs.CV updates on arXiv.org
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