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Innovation and Implementation Science

Artificial Intelligence

The amount of data has grown exponentially over the past years, also in medicine and of course in nephrology. How to make sense of them?

AI programs are programs with the ability to learn and reason like humans, enabled applications in kidney diseases.

We are dealing with an old problem….how to make sense with the many inputs we receive?

The answer is how to make good predictions.

And decoding the genomes: predicting the effect of any mutation.

A very good example is Covid-19 and Diabetic Kidney Disease (DKD). Patients with diabetes have acute excess morbidity and mortality of Covid-19. At the same time Covid-19 is associated with higher incidence of acute kidney injury (AKI). How is the kidney targeted? Why are DKD patients are so vulnerable to Covid-19? It seems that SARS-CoV-2 receptor networks in diabetic and Covid-19 are associated with kidney disease.

New tools have been introduced:

  • Machine learning (algorithms that allow a program to learn from its own mistakes) to medical research and practice for many biological contexts
  • Deep learning
  • Prediction model for health records
  • Risk prediction models need to be constracted and validated with an eye of detail
  • Decision trees and forests
  • Implementation of precision medicine in DKD

This section aims to demonstrate nephrologist’s view and experience in all,the above areas of interest. News, published and unpublishes data, related articles will be the components of this section. This series of articles aims to examine the complex relationship between “new technologies” and the kidney across the spectrum of renal care.

Artificial Intelligence and Kidney: Diabetic Nephropathy example