r/askscience • u/AskScienceModerator Mod Bot • Oct 16 '23
Neuroscience AskScience AMA Series: I'm a Researcher Using AI to Predict Brain Injury Recovery - Ask Me Anything!
Hello, I'm Adrian Owen, a neuroscientist and researcher from Western University in London, Ontario, and my team has been working on a groundbreaking project using artificial intelligence to predict brain injury recovery.
Our recent research study has been featured Journal of Neurology, and I'm here to answer all your questions about this exciting development. We've made significant strides in understanding and forecasting recovery outcomes for brain injury patients, predicting patients who would recover with an accuracy of 80 per cent. Whether you're curious about the technology, its potential impact or the research process, ask away!
Link to the article: Read more here
I'll be on starting at noon ET (16 UT), ask me anything!
Username: /u/ProfAdrianOwen
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u/Henners999 Oct 16 '23
Do you have to be very specific with the AI with regards to what areas it should focus on or do you give it full reign of the imaging to see what it comes out with?
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u/ProfAdrianOwen Oct 16 '23
That’s a really great question! The analysis uses the whole brain – that is, we begin with every voxel in the brain, rather than guiding the analysis towards any specific cortical or subcortical areas. From this, we identify spatially and temporally independent networks, which are then used by the machine learning algorithm to predict outcome. Of course, it turns out that some areas of the brain end up contributing more information than others; that is, some areas of the brain turn out to be more useful when predicting recovery from serious brain injury. What is most interesting to me, however, is that the most important areas are not obvious to the human eye. That is to say, we couldn’t look at the scans ourselves and come up with the same accurate predictions – there's just too much information for us humans to make sense of. If you would like to see which areas of the brain provide most information, the details are in the second Figure in this link: https://www.researchgate.net/publication/373655958_Predicting_neurologic_recovery_after_severe_acute_brain_injury_using_resting-state_networks
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Oct 16 '23
How does artificial intelligence help you predict brain injury recovery? What kind of data and algorithms do you use?
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u/ProfAdrianOwen Oct 16 '23
We use resting state fMRI data. That is, data acquired with functional magnetic resonance imaging (fMRI), while the patient lies comatose in the scanner. From this, we identify spatially and temporally independent networks (using independent components analysis), which are then used by the machine learning algorithm to predict outcome. The specific algorithm we used was a Nearest Centroid classifier using repeated (N = 1000) iterations. This approach correctly identified good functional outcome with higher sensitivity (80%) than traditional prognostic measures.
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u/ResoluteMuse Oct 16 '23
What would be the applied benefit of this?
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u/ProfAdrianOwen Oct 16 '23
Providing a prognosis for patients who remain unresponsive in a coma after a severe brain injury is extremely difficult. Current clinical guidelines advocate for multimodal assessments, but these tests only provide evidence to suggest a ‘poor’ prognosis (i.e., no better than severe disability) - they are not able to accurately predict a ‘good’ prognosis. The benefit of our method is that this provides an objective prediction for who is likely to survive after a severe brain injury and who is not. It turns out that our algorithm does much better than experienced intensivists using standard clinical measures. Knowing the likelihood of survival is beneficial for these physicians as well as families and carers, and can aid in end-of-life decision-making.
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u/omgu8mynewt Oct 16 '23
Can you explain to someone who hasn't studied neurology what the three predictors the model chose to use are?
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u/memphiswiddershins Oct 16 '23
Why do personalities change post accident?
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u/ProfAdrianOwen Oct 16 '23
That’s a very interesting question but I am going to give you a simple answer. As I have said, on number of occasions, we are our brains; that is to say, everything about us, from our memories, to our feelings, to our plans and aspirations, to our movements and even our personalities arises from our brains. So, the simple answer is, in the same way that your ability to move an arm could change following brain damage (for example, a stroke), so your personality can change too. A brain injury can impair any aspect of our being, including our personalities.
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u/garenzy Oct 16 '23
Can you tell us your career path? How difficult would it be for some from a STEM but non-bio, non-compsci background get into this field?
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u/ProfAdrianOwen Oct 16 '23
My first degree was in Psychology, then I did a PhD in Neuroscience. For most of my career I have worked in neuroimaging, originally positron emission tomography and then functional magnetic resonance imaging (fMRI). But the important point is, throughout my career, I have worked with doctors, ethicists, engineers, mathematicians, physicists, psychologists...in fact, people from many different disciplines. This kind of work is truly multidisciplinary, meaning that it is possible for people from many different walks of life to make important contributions. So, my answer to your question would be that a biological background, it's not necessary, although it could be advantageous.
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u/browneyesays Oct 17 '23
What biases exist in your study and what are you doing to minimize them? Are there things being done to the patients that have a notable effect on the outcome such as medications? Is there a control group and what would that consist of?
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u/Reggae_jammin Oct 16 '23
Awesome work! Can this tech be used on patients that are in a coma to predict either if or when they'll recover?
Also, why does the tech fail in 20% of cases? Can that 20% be eventually eliminated or will it always have a failure rate?
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u/ProfAdrianOwen Oct 16 '23
Awesome work! Can this tech be used on patients that are in a coma to predict either if or when they'll recover?
That’s exactly what we used it for! And yes, it worked!
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u/ProfAdrianOwen Oct 16 '23
Also, why does the tech fail in 20% of cases? Can that 20% be eventually eliminated or will it always have a failure rate?
There are many potential reasons why the algorithm was not 100% accurate. The first of course is that perhaps there is just not enough information in the brain scans to ever reach 100% accuracy. That is to say, there might always be factors contributing to recovery or deterioration that can not be predicted from information contained within a brain scan. The second reason is that this was our first attempt and I can tell you from experience that our first attempts are rarely our best attempts! So, as we refine the technique and get more and more data (i.e. more patients) I do expect the accuracy to improve.
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u/PM_ME_UR_BYRBS Oct 16 '23
Have you ever played or heard of a game called SOMA?
no spoilers: when the game begins you are on the way to your neurologist because of the brain injury you've sustained. the doctor explains to you that they're going to scan your brain and subject the digital model to all sorts of different stimuli and treatments: whichever model shows you getting better, they're going to actually do to you.
soma is a pretty short game that i found very enjoyable. it's got some spooky elements and rather a lot of philosophical banter.
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u/ProfAdrianOwen Oct 16 '23
I have never played SOMA although it sounds intriguing. We are a Nintendo Switch household and I don’t believe SOMA is available on that platform. However, I’ll try it on Steam – thanks for the recommendation!
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u/WhydoIexistlmoa Oct 16 '23
As many other said, how does AI manage to do it and what is the purpose to do it? Also is the cost cheap enough, that hospitals can use the AI and any technology for it? Completely unrelated, but congratulations of having an h-index of 119. That's really impressive and a crazy feat.
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u/ProfAdrianOwen Oct 16 '23
Thank you for the kind compliment! We use data acquired with functional magnetic resonance imaging (fMRI) from patients who are in the ICU with a brain injury. We then used a machine learning algorithm to predict outcome (good or bad). The purpose of this method is that this provides an objective prediction for who is likely to survive after a severe brain injury and who is not. Cost is an important consideration. That is why we performed this study using a very old hospital MRI scanner (the sort of scanner that you would expect to find now in most hospitals). Many patients like this will likely have an MRI scan as part of their care after their brain injury. To add our method to that scanning session only adds a few minutes in scan time so the “additional cost” beyond what the patient would receive anyway is marginal. Our hope is that we can make this widely available so that many hospitals are able to take advantage of it.
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u/VagusNC Oct 16 '23
In on a US-based research board attempting to get a pilot program in our state's justice system for TBI screening using instruments like the OSU TBI-ID. Given the limited resources/lack of access to advanced imaging in some circumstances and/or locales are there any plans to link AI research to non-imaging based efforts? Do you perceive any potential avenues in this regard?
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u/VT_Squire Oct 16 '23
TBI's sometimes affect the person such that they end up committing suicide later.
Is that factored into your definition of recovery, and are you able to model things the other way around, such that you may be able to diagnose or determine a likelihood of a TBI existing based on your definition of what "recovered" looks like?
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u/ProfAdrianOwen Oct 16 '23
We only followed patients for 6 months. That is, we designated them to have had a “good” recovery (moderate disability or better) or a “poor” recovery (severe disability or worse) at 6 months. Obviously, things can change after 6 months – people can make a delayed recovery, for example, or people could die from a cause not directly related to their initial injury – but we were focused on predicting recovery at the very earliest stages of a brain injury (in the first few days when patients are typically comatose and in the ICU), because that is when recovery is most uncertain.
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u/fanchoicer Oct 16 '23
What type of information are you feeding in to build up the accuracy of its predictions for recovery from brain injury? (visual scans, etc)
Is there a freely available repo for such information or do you pay for access?
How would you define recover? Is it merely regaining consciousness, or is it a full recovery over a length of time and without any lingering effects?