Practical Deep Learning for MDs

What is the point of this?

In medicine, we collect data from patients (Hx, Ex, Ix) to make meaningful conclusions (Dx, Mx). Data analysis tools like Deep Learning have shown success (CXR, sepsis ICU?) and failure (EPIC & sepsis) in helping us derive meaningful conclusions better.

It’s my belief that clinicians should be equipped with the basic knowledge of how it works, its benefits and limitations, so we can safely and confidently use it in our clinical practice. This website is a resource to do just that - to bridge clinical practice and emerging tools.

Often, clinicians encounter new papers in journals that outline groundbreaking discoveries regarding the application of deep learning in their field. However, due to the limitations of academic papers, they often fail to provide intuitive explanations of fundamental concepts such as what a neural network is. On the other hand, technical papers are far too unapproachable. In this website, I break down influential papers in each field and show you exactly what is going on behind the scenes.