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Found 5 papers, 2 papers with code
Caveats in Generating Medical Imaging Labels from Radiology Reports
Acquiring high-quality annotations in medical imaging is usually a costly process.
A Strong Baseline for Domain Adaptation and Generalization in Medical Imaging
This work provides a strong baseline for the problem of multi-source multi-target domain adaptation and generalization in medical imaging.
Efficient and Accurate Abnormality Mining from Radiology Reports with Customized False Positive Reduction
Obtaining datasets labeled to facilitate model development is a challenge for most machine learning tasks.
Weakly Supervised Medical Diagnosis and Localization from Multiple Resolutions
Diagnostic imaging often requires the simultaneous identification of a multitude of findings of varied size and appearance.
Learning to diagnose from scratch by exploiting dependencies among labels
The field of medical diagnostics contains a wealth of challenges which closely resemble classical machine learning problems; practical constraints, however, complicate the translation of these endpoints naively into classical architectures.
