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Found 4 papers, 1 papers with code
The role of noise in denoising models for anomaly detection in medical images
Denoising methods, for instance classical denoising autoencoders (DAEs) and more recently emerging diffusion models, are a promising approach, however naive application of pixelwise noise leads to poor anomaly detection performance.
Paying Per-label Attention for Multi-label Extraction from Radiology Reports
Training medical image analysis models requires large amounts of expertly annotated data which is time-consuming and expensive to obtain.
Ontological attention ensembles for capturing semantic concepts in ICD code prediction from clinical text
We present a semantically interpretable system for automated ICD coding of clinical text documents.
Language Transfer for Early Warning of Epidemics from Social Media
However, the data required to train models for every language may be difficult, expensive and time-consuming to obtain, particularly for low-resource languages.
