This is how AI will change healthcare
Automatization, robots, and new medication
Hey there,
As a futurist, AI in healthcare has been a major theme in my work.
On stage during a keynote, in a workshop where doctors and healthcare professionals practically engage with it, and in interactive sessions about what this all means for the work in healthcare.
In this newsletter, I share three ways in which AI can radically change healthcare.
And yes, I think the insights are interesting even if you don't work in healthcare 😀
Enjoy reading,
Peter
P.S. The company Vitestro is working on autonomous blood collection devices. Check out my interview with the two founders and my first impressions of the device.
For English subtitles: select the icon of a sprocket (settings), and then subtitles. 🇺🇸
How AI changes healthcare
Image analysis, such as the assessment of radiological images, is one of the most well-known applications of AI in healthcare. It was even a theme back in 2009, when I, as a business student, conducted my graduation research at the Department of Radiology at the UMCG in Groningen, the Netherlands
But besides analyzing images? What are notable changes brought by AI in healthcare? Here are my insights:
1. Automation
A few weeks ago, I was at a healthcare conference in Utrecht, the Netherlands. In the conversations over coffee, in workshops, and at the stands on the exhibition floor, the main theme was AI.
What struck me is that most tools focus on automating work processes. The holy grail here is primarily to reduce the administrative burden on healthcare professionals.
Good examples, in my opinion, include:
An AI model that supports and automates the coding of day admissions;
Tools that convert spoken text into usable documentation.
One of the things I realized with these examples is that it should not lead to a reflex: if AI enables us to record more in our administration, then we must always do it.
It seems to me that it should be both: using AI tools to automate things, but also thinking about our way of working.
2. Robotization
The company Vitestro calls the device from my video ‘an autonomous blood collection device’.
Not a blood collection robot.
In the interview, the founders told me that initially, it was expected that most people would have negative associations with the word robot. Think of movies like Terminator or 2001: A Space Odyssey.
However, during the first tests with patients, this sentiment turned out to be quite mild.
Remarkable Robots
Besides the use of robots devices for drawing blood, here are a few notable applications:
This Chinese robot that can place implants in the teeth;
Big tech is working on humanoid robots: Nvidia trains robots in project Gr00t with multimodal inputs, Tesla is working on Optimus, and OpenAI is developing robots with Figure. What role do these players want to take in healthcare?
With the increasing shortage of staff in healthcare, I expect more and more healthcare organizations to look into robots.
But it's not a panacea: besides the investment, it also requires installation, maintenance, training, and space to learn.
3. New Medication
In 2016, AlphaGo, an AI system that taught itself the rules of Go, defeated the best human player in the game at that time.
(In the Deep Dive below, I recommend a documentary about it. 👇)
This breakthrough motivated DeepMind, the creators of AlphaGo, to tackle a much harder challenge: the folding of proteins.
The sequence of amino acids determines not only the formation of a protein, but also the way the protein is folded.
And this folding is crucial: it determines what the protein does and what other molecules can do with the protein.
From Fold to Medicine
The goal of medicines is to block certain molecules or to stimulate them. Biologists and pharmacists, therefore, want to know how proteins are folded.
Using various methods, scientists have mapped about a hundred thousand protein structures over the past fifty years. Until AlphaFold: this program makes detailed predictions about the folding of more than 600 million protein structures.
The expectations are therefore high. With this knowledge, it is much faster, easier, and cheaper for medical biologists to test promising combinations of molecules as a basis for a new drug.
In short: AI predictions of protein structures = new medication.
Explainer
Sabine Hossenfelder made this video about the problem of protein folding and whether AlphaFold is the solution.
Deep Dive on AI & Work
Articles, books, podcasts, videos, documentaries, and more on this theme.
1. READ / These previous newsletters I wrote about artificial intelligence in healthcare:
2. READ / In his book Co-intelligence, Ethan Mollick writes about the emergence of Generative Pre-trained Transformers (GPT) models and what they mean to us as humans, work, society, and domains such as healthcare.
3. WATCH / Lee Sedol is the best Go player ever. The documentary AlphaGo (rated 7.8 on IMDb) captures the challenges and tensions during the historic match between him and DeepMind's AI system.
I recently rewatched the documentary. Although it was released in 2017, it remains relevant and interesting.
Particularly famous is move 37 in the second match, Sedol's reaction, and the perspective it provides on the (further) development of artificial intelligence.
🙏 Thank you for reading
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