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PM_ME_VINTAGE_30S@lemmy.sdf.org ⁨1⁩ ⁨month⁩ ago

Haven’t read any article about this specific ‘discovery’ but usually this uses a completely different technique than the AI that comes to mind when people think of AI these days.

From the conclusion of the actual paper:

Deep learning models that use full-field mammograms yield substantially improved risk discrimination compared with the Tyrer-Cuzick (version 8) model.

If I read this paper correctly, the novelty is in the model, which is a deep learning model that works on mammogram images + traditional risk factors.

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FierySpectre@lemmy.world ⁨1⁩ ⁨month⁩ ago

For the image-only DL model, we implemented a deep convolutional neural network (ResNet18 [13]) with PyTorch (version 0.31; pytorch.org). Given a 1664 × 2048 pixel view of a breast, the DL model was trained to predict whether or not that breast would develop breast cancer within 5 years.

The only “innovation” here is feeding full view mammograms to a ResNet18(2016 model). The traditional risk factors regression is nothing special (barely machine learning). They don’t go in depth about how they combine the two for the hybrid model, so it’s probably safe to assume it is something simple (merely combining the results, so nothing special in the training step)

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- errer@lemmy.world ⁨1⁩ ⁨month⁩ ago
  ResNet18 is ancient and tiny…I don’t understand why they didn’t go with a deeper network. ResNet50 is usually the smallest I’ll use.
  
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- PM_ME_VINTAGE_30S@lemmy.sdf.org ⁨1⁩ ⁨month⁩ ago
  
  They don’t go in depth about how they combine the two for the hybrid model
  
  Actually they did, it’s in Appendix E (PDF warning) . A GitHub repo would have been nice, but I think there would be enough info to replicate this if we had the data.
  
  Yeah it’s not the most interesting paper in the world. But it’s still a cool use IMO even if it might not be novel novel enough to deserve a news article.
  
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llothar@lemmy.ml ⁨1⁩ ⁨month⁩ ago
I skimmed the paper. As you said, they made a ML model that takes images and traditional risk factors (TCv8).

I would love to see comparison against risk factors + human image evaluation.

Nevertheless, this is the AI that will really help humanity.

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