AI Healthcare: An algorithm that can spot cause and effect could supercharge medical AI

I wasn’t expecting MIT Review to spout nonsense but trawling through the web, I occasionally stumble upon a lot of articles that always speak about the “potential”. It is relatively easier to write the algorithm but parsing the data is a different level problem altogether.

Babylon has been under cloud for making outrageous claims earlier. I have worked with another UK-based company (I can’t name them) and I was quite surprised that their “recommendation” for symptoms only directed towards the “nearest practitioner”. So, practically, they had a database of primary care physicians and only worked on the location metadata but marketing it having an AI engine! Ridiculous!

Researchers Anish Dhir and Ciarán Lee at Babylon Health, a UK-based digital healthcare provider, have come up with a technique for finding causal relations across different datasets. This could allow large databases of untapped medical data to be mined for causes and effects—and possibly the discovery of causal links that we did not yet know about.

An algorithm that can spot cause and effect could supercharge medical AI – MIT Technology Review

Read it at your peril!