By Dr. David E. Marcinko MBA MEd CMP
SWARM INTELLIGENCE IN MEDICINE
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Warm Learning or Swarm Intelligence, is how swarms of bees or birds move in response to their environment.
When applied to data there is “more peer-to-peer communications, more peer-to-peer collaboration, more peer-to-peer learning and that’s the reason why swarm learning will become more and more important as … as the center of gravity shifts” from centralized to decentralized data.

Medicine Example:
Consider this example, “A hospital trains their machine learning models on chest X-rays and sees a lot of tuberculosis cases, but very little of lung collapsed cases. So therefore, this neural network model, when trained, will be very sensitive to what’s detecting tuberculosis and less sensitive towards detecting lung collapse.”
“However, we get the converse of it in another hospital. So what you really want is to have these two hospitals combine their data so that the resulting neural network model can predict both situations better. But since you can’t share that data, swarm learning comes in to help reduce that bias of both the hospitals.”
And this means, “each hospital is able to predict outcomes, with accuracy and with reduced bias, as though you have collected all the patient data globally in one place and learned from it.”
Moreover, it’s not just hospital and patient data that must be kept secure. What swarm learning does is to try to avoid or reduce the sharing of data, or totally prevent the sharing of data, to [a model] where you only share the insights, or you share the learnings.
So, that’s why it is fundamentally more secure.
YOUR COMMENTS ARE APPRECIATED.
DR. GOH PODCAST: https://www.technologyreview.com/2021/08/16/1031738/a-new-age-of-data-means-embracing-the-edge/?mc_cid=30af99395f&mc_eid=72aee829ad
Thank You
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