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Found 5 papers, 2 papers with code
Automated clinical coding using off-the-shelf large language models
The task of assigning diagnostic ICD codes to patient hospital admissions is typically performed by expert human coders.
Compositional Representation Learning for Brain Tumour Segmentation
For brain tumour segmentation, deep learning models can achieve human expert-level performance given a large amount of data and pixel-level annotations.
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.
What is Healthy? Generative Counterfactual Diffusion for Lesion Localization
This requires training with healthy and unhealthy data in DPMs.
Attaining human-level performance with atlas location autocontext for anatomical landmark detection in 3D CT data
We present an efficient neural network method for locating anatomical landmarks in 3D medical CT scans, using atlas location autocontext in order to learn long-range spatial context.
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