Among the many examples of Artificial Intelligence, AI in healthcare is clearly one of the leaders. AI is already reshaping medicine in many ways, and its influence will only increase in the years ahead.
We spoke about:
- Key ways that AI is being used in Healthcare.
- How to select an AI solution for your company.
- The future of AI in healthcare.
See below for transcribed highlights of “AI and Healthcare” with Krishnan Nandabalan.
How Artificial Intelligence is Changing Healthcare
Use Cases for AI in Healthcare
“One of the major areas where a lot of investment is being noticed is in robotics-assisted surgery, typically in microsurgery. Now, here is a field where it’s natural extension of the AI capabilities. So, that allows you to actually use robotics more efficiently when you’re performing a bypass surgery or some very, a microsurgery in the brain which needs a high deal of precision. You still need the experienced surgeon out there to make sure that everything is being done right but, now, instead of human hands, you can have a very precise machine that’ll be doing the job for you.
“Some of the novel treatments and deep brain stimulation in Parkinson’s, for example, is being done using these techniques. The other interesting area where AI is being applied in a healthcare platform is really in fraud detection. So, if you see too many of one type of medication coming out from a center that are what seems other than normal, you can immediately have an AI system detect that and warn that it could be real or it could be false but at least it behooves us to go and investigate it.”
“In the short-term, the [uses of AI are] all towards increasing the efficiency and decreasing the error. So it’s not as we’re coming up with a totally new thing that we don’t comprehend. It’s just actually taking our human experience and magnifying it or amplifying it such that you’re reducing the error, increasing the efficiency. Hopefully, ultimately reducing the cost because the way the cost is increasing, it’s kind of unsustainable.”
AI and Machine Learning
“There’s a lot of conflation between AI and machine learning, when we talk about it. One very simplistic way to distinguish between the two is: AI is about taking the existing human knowledge and experience and essentially turning it over to the machines so that they can use it in an automated, faster, efficient, cheaper, better, way.
“Machine learning is a subset of that where you’re actually taking all the current experience and providing it to the machine in a certain set of algorithms. And ask it to learn more based on the data that’s been gathered on a daily basis. So, especially in healthcare, that’s gonna be very useful when you’re thinking about chronic diseases. So, diabetes, obesity, Alzheimer’s, even other cardiovascular diseases where, currently, we seem to treat some of those diseases better than others but is there more to be learned based on all the data that’s been gathered?”
“So, this is where AI becomes now a part and parcel of this learning process and you want to actually bring in techniques like machine learning, deep learning, neural networks and so on to actually gain more insight into the data that we collect on a daily basis.”
Advice on Selecting an AI Solution
“You can actually start scanning and monitoring developments in the fields that you’re interested in to see how are these being applied. Teaching hospitals, for example, are they using this? Are companies beginning to use such devices in their clinical trials? Are more patients asking for it?
“So, there are vendors that specialize in coming up with algorithms that are used in diabetes or in sleep disorders, or in movement disorders like Parkinson’s and things like that. And these companies, while they may not develop the hardware like Apple iWatch or something else, they are more conversant with algorithms needed to actually help the patient.
“So, if you are a big pharma company who’s developing or who has a franchise of drugs to cater to one therapeutic area, you need this entire ecosystem. It’s not just the big tech players, they are needed. It’s not just these smaller vendors who are very specialized, they are needed as well. And then, you also need the biotech and the early stage companies that are now exploring all of these technologies and really moving it upstream in the discovery process.”
AI and “Augmented Intelligence”
“There’s another way of [thinking about] AI. It’s not really artificial intelligence, it’s augmented intelligence. We’re actually augmenting the human experience or the human capability. And because of the digitization of the world around us, we are using our smartphones for everything, we are recording all of our daily tasks through the phone, we’re communicating everywhere. It’s inevitable that now that [AI] is going to permeate healthcare. And it’s just the next step in the evolution.
“I think it’s a very efficient way of utilizing all the data that is generated and currently is not being used.”