Could Machine Learning Save Our Health Care Program? Let’s Read and Learn
We are very quickly going to reach a tipping point where AI can transform health care. This is a research project at the moment. But the potential is enormous. For the NHS (National Health Service), machine learning could mean better care and lower costs as machine learning take on some of the jobs done by doctors. Their power comes from not just analyzing images in milliseconds but learning from the data they collect.
Deepmind Is leading the way in AI not just in the UK but in the world. It was set up by three partners in 2010. Four years later it was bought by Google for £400 million. — four years later. This gives us a sneak preview into a new type of health care that patients laugh. But it also unnerves people worried about medicine slipping into corporate control. Mustafa Suleyman, one of the founders talk about the company’s project with the NHS. He said “what I am really worried about is that the fear and the reactionary paranoia is going to limit the access to what is clearly going to be an incredibly valuable technology which will change people’s lives.”
Learn From The Applied Machine Learning in the UK
In the UK the total cost of blindness is £28 billion every year. Equal to a fifth of the health Budget. Everyday, 220 people go blind because of macular degeneration, a completely treatable condition when caught in time. The Royal College of ophthalmologists says patients with and acute vision should be seen within two weeks. But the NHS is falling short of this guidance.
At Deepmind the technology they are pioneering is getting machines to teach itself. Last year, in a ground-breaking moment, a computer outsmarted the best human brain in the ancient Chinese game of Go, the holy grail of artificial intelligence. This game is special because there are more possible moves than they are atoms in the universe. So there is no way of calculating every option on the board. Instead, the machine have to mimic, learned from experience, a little bit like the human brain. Every time it did this it got better and eventually it beat the Grand Master.
Now the same technology is being used to save people’s sight. Elaine knows all about the trauma that can bring. 15 years ago she started to go blind in her left eye.
“She said “I remember it. I was walking along a path in the woods. The shadows were getting darker and darker. Everything was getting dimmer and dimmer. And I felt less than a person. I felt… I felt alienated from everybody else.”
Then just three years ago Elaine faced the prospect of losing the sight and have the eye, as well.
She said “I waited maybe six to eight weeks for an appointment, worrying all the time that something dreadful was going to happen to this I. Just thinking about what the consequences would be if you are blind you are vulnerable. And life for me, then, would not have been worth living, it really wouldn’t.
Machine Learning in Action
Thanks to AI it has turned out to be a very different story for her. She was one of the first AI test studies at Moorfield. And now, instead of living in the shadows she spends her time in the clouds. She is raising money for other patients facing blindness.
This is AI in action. It looks like a normal scanner but inside there is a machine learning a tool that can analyse thousands of complex images almost instantly. They show not just the back of your eye but the cross-section of the retina at a higher magnification than an MRI machine. Hours of work for a person, just a few seconds for an AI machine.
A commonest cause for blindness in the UK is called Age-Related Macular Degeneration (AMD). The thing about AMD is that nearly 200 people every single day, just in the UK, develop the blinding forms of AMD. The Royal College of ophthalmologists suggest these patients should be seen and treated within two weeks of the onset of their symptoms. The reality is that on the NHS that target isn’t being met. Machine learning would allow us to identify those patients and get them treated not just within the two weeks, but potentially within two days.
Artificial intelligence is a remarkable achievement. You can see that in a place like this. But with it comes some very serious dilemmas. Will people ever accept mistakes made by machines because there will be some? And when those mistakes take place in who is responsible, the machines, or the people behind them?
There has been a problem over lack of clarity and liability issues when you get into things like machine learning. If you take something like health care, within a short space of time it may well be negligent for a doctor not to use an AI aid. But in that situation who is to say who is liable? Is it the machine, or visit the doctor who hasn’t really assessed whether or not the outcome of the tool is valid? These are difficult issues. It always has to be the doctor who remains liable.
Experts’ Opinion About Machine Learning and Artificial Intelligence
Roger Bickerstaff, a technology lawyer, said “we’ve already seen it in an interesting experiment in Sweden where some sort of machine learning bot was let loose on the dark web. It was given 100 euros per week to go and spend on the dark web. It went off and bought some firearms, and some surveillance equipments. The authorities found out about this thing and came in and arrested it. Of course, you cannot arrest a machine, but we hear these things, and ascribe liability to machines, when, of course, the things being done really the responsibility of the people who set spot free.”
Whaever the doubt, AI is now being used in specialties beyond ophthalmology despite the doubt. At this hospital it is being trialed in both heart surgery and pioneering fetal scans. What artificial intelligence allows us to do is to capture the training and experience of thousands of people very quickly. — and pioneering fetus scans. We can capture a lot more than any single person could capture in a lifetime.
For Rebecca Hooper and many other mothers, these scans show details never seen before. A lot of the healthcare systems we have are overwhelmed. We are talking about millions of pictures being created at each center where the scanning is being carried out. It’ll help you to see if there is anything wrong with the baby.
But if AI can do all that, is this the end for doctors? You have to think about the systems as being tools. Just like scanners and scalpels. They are assistants which help humans to do better. Despite the progress at Moorfields, Deepmind has been brought into controversy after a hospital was given access to the information of patients and doctors. But it raised doubts about whether such a big project should be awarded to a commercial organisation, despite it having nothing to do with AI. It leads to some questions about privacy for Deepmind.
Economists now describe data as the new oil. A 21st-century commodity which will be the driver for wealth of companies. The question is will this be at the expense of individuals? Do you think machines will help humanity, or will it entrench inequality? We have to think sensitively about any new technology that is introduced. If we don’t introduce it wisely, it will entrench the existing order, put it that way. If we care about equality we should definitely start to think now and that’s the right time, who benefits from that technology and how you can ensure those benefits are as widely available as possible.
Machine learning can seem like it has been borrowed from a sci-fi script, but this type of medicine is coming faster than you think. There are huge gains to be made by patients and taxpayers alike, but there are risks, too, because those gains depend on us giving up some of the secrets of our medical history to corporations we may not be able to control.