📜🌳 -->🍃🍃: MoDN Published in PLOS Digital Health

We break down a neural network into a sequence of modules...

🌳 -->🍃🍃🍃🍃🍃🍃🍃🍃🍃🍃🍃🍃🍃

...to create MoDN: Modular Clinical Decision Support Networks.

See publication on PLOS Digital Health

👆 Check out our publication in PLOS Digital Health 📜 to see how MoDN allows the flexibility to adapt to volatile resource availability in constrained settings, where the clinician:

1) Could compose models at the bedside using whatever number or combination of inputs (questions/tests) are available to them #composability #mixnmatch 🔀

2) Add new inputs without needing to retrain the entire model #compartmentalization 🎡

3) Learn from the notoriously flawed data derived from clinical decision support tools #systematicmissingness 👻

🏆 Phenomenal work by studentpower: Cécile Trottet and Thijs Vogels

🏥 Thank you to our clinical collaborators Alexandra Kulinkina, Rainer Tan, Ludovico Cobuccio

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❤️ This work was funded by Fondation Botnar as part of the Dynamic Study

TrottetVogels2023_MoDN

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