This is an interesting paper (and worth your time) to pursue about the key challenges for AI in healthcare. It gives a decent overview of the landscape. Artificial intelligence (AI) research in healthcare is accelerating rapidly, with potential applications being demonstrated across various domains of medicine. However, there are currently limited examples of such techniques being successfully deployed … Continue reading AI healthcare: Key challenges
Someone had shared this link with me on Telegram. I have kept a distance away from writing about the viral pandemic, so far, but this news raised several disturbing issues. I have rallied against the existing model of academic publishing and glorified statistics/ tweetorials that have increasingly gained “acceptance” as the new normal. Not surprisingly, … Continue reading Moderna’s favourable coronavirus vaccine trial results are an example of ‘publication by press release’
I stumbled on this fascinating write-up and I'll try to revisit this idea later. However, the vexed issue of "cancer research" rears its head again- we would need an incremental and exponential increase of dollars in "funding" before we are able to strike out something substantial. However, the research is being pushed out in the … Continue reading Is It Getting Harder for Research to Boost Productivity?
Genetic testing is flawed (mostly)
It is a brilliant write up! Briefly, there are two fundamental approaches to AI. Connectionism- Look at historical data. Draw inferences from "patterns." Symbolism- First look at this research proposal from 1958 to understand its context. It seeks to map concepts between words and numbers. For example, neural networks. In isolation, none of the approaches … Continue reading AI and Healthcare: Why it is essential to study its past?