7 ms·

AI predicts if and when someone will experience cardiac arrest

96 points by hhs 5y ago

nodesocket 5y ago
I am absolutely clueless about heart medicine, but it seems like having monitoring of heartbeat in real-time should be able to predict potential anomalous and problems. I expect that Apple with watch will dramatically be able to save lives in the future with their products.
- deleted 5y ago
  [deleted]
- agumonkey 5y ago
  The few that I got is that cardiac electrophysiology is still mysterious and can derail in weird ways even if you look at it closely.
- gleenn 5y ago
  Apple is quick to tell you all the things that the heart monitor can NOT do, but I think they have already had cases where the watch detected peculiarities in heart rhythms and suggested getting things checked out by a doctor which did save lives. https://wccftech.com/apple-watch-saves-life-of-a-70-year-old-woman-with-afib-heart-condition/ https://wccftech.com/apple-watch-saves-life-of-a-70-year-old...
- macintux 5y ago
  I’m reminded of someone who insisted in a thread here that heart rate monitoring on Apple Watch was stupid because they could just check their own whenever they wanted to.
- mjmj 5y ago
  Yeah, That’s the dream and already happening as far as heart rhythm abnormalities. But wearables are pretty lacking. For example, I have a resting heart rate of 40bpm due to intense exercise. Iwatch won’t register heart rates that low, but if I get an EKG I’m fine. Additionally EKG’s puts leads all over your chest to get precise electrical measurements. A watch on your wrist isn’t going to be comparable, esp with things like sudden cardiac death. This article takes it even further as you need detailed imaging to really save these types of patients. Since we don’t yet know many of the underlying genetic variants or causes of sudden cardiac death. It’s more common than people realize and often goes undiagnosed or misdiagnosis because it’s hard to detect until too late. Source: Multiple people in my family have died from sudden cardiac death. All with perfectly normal EKG’s before they passed.
earleybird 5y ago
My very tangential observations in the cardiology domain is that it is in some respects a dark art that requires years, perhaps decades of experience to understand underlying mechanisms. While this certainly looks promising in a person / not person recognition kinda way; I'm hoping it can shed some insight the interaction between scarring and conductivity that leads to arrhythmias.
- jrapdx3 5y ago
  Your observation about practicing medicine being a "dark art" has a lot of merit. As such the idea applies to most if not all medical specialties and I strongly suspect is no less true among science-based disciplines in general. In health care domains we desperately want to believe providers know precisely what they're doing. It's particularly vexing to find out that "facts" are surrounded by an intrinsic level of uncertainty. IOW whatever action a practitioner deems best in a given situation is a judgement call grounded in experience. Sure, that's bolstered by underlying science, systematic investigations and published reports, but still there's no escaping the probabilistic nature of knowledge in the fields of medicine. The provider you want to have is one who strives to do what's possible up to the limits of techniques and technology, and above all seeks to learn from every patient encounter.
- Smileyferret 5y ago
  I don’t disagree with you that much of medicine is hand-waving and voodoo magic, but arrhythmias due to scar tissue likely have a similar mechanism to other well-studied arrhythmias. Overall I think that cardiology has some of the more scientific explanations of its pathophysiology than other fields. Scarring simply interrupts smooth conduction of impulses throughout the myocardium and makes it more susceptible to arrhythmias. If you want to see a similar mechanism explained, check out this video: https://youtu.be/j8pVU9snSH4 https://youtu.be/j8pVU9snSH4
  - earleybird 5y ago
    Thanks for the link. I need to choose words better - rather than "dark arts" I probably should have said "tacit knowledge". I certainly didn't mean to imply that arrhythmias are not well studied, rather, my hope is that we can use AI methods to do better science. side note: I know EEs who claim antenna design is a black art :-) It also is well studied and yet according to some, it appears magical at times.
carbocation 5y ago
I haven't read the research article yet, but since the jhu.edu article doesn't link to it, here it is: https://www.nature.com/articles/s44161-022-00041-9 https://www.nature.com/articles/s44161-022-00041-9
- donttellitsme 5y ago
  Thanks for the link. Unfortunately it does not seem to be on sci-hub (yet?) and apparently my institution doesn't want to pay for nature anymore. While I have no doubt that imaging-based neural nets can outperform a lot of the cardiac risk scores in clinical use today (they are usually pretty rudimentary), I would be fairly cautious about this article. Let's say one of the authors has a pretty long record of making extraordinary claims backed by very little evidence; managing to impress the medical community while at the same time being regarded as an impostor in the computer science community. Of course I'm just a random stranger on the internet, so I might just be a jealous competitor ;)
  - carbocation 5y ago
    I have a Harvard library login and ran into the same issue (tried sci-hub as well, no luck).
antihero 5y ago
Pretty cool and terrifying if they made it an app I guess
- deleted 5y ago
  [deleted]
- Teknoman117 5y ago
  I mean, it requires heart imaging, which you're not going to be getting without access to some very expensive equipment (assuming you just randomly wanted to look at this rather than getting images back from your doctor).
qchris 5y ago
I'm generally pretty skeptical of claims of applying machine learning to improve healthcare outcomes (they often seem to be a poorly thought-out veneer), but at first glance, this one actually seems pretty exciting. It also seems like it's more of a "machines aiding humans, not replacing them" situation which, especially in context of healthcare, is always nice to see. > Current clinical cardiac image analysis extracts only simple scar features like volume and mass, severely underutilizing what's demonstrated in this work to be critical data. > "The images carry critical information that doctors haven't been able to access," said first author Dan Popescu, a former Johns Hopkins doctoral student. This is, like, the thing that machine learning is really good at--pulling out additional information from complex patterns represented as imagery. It's a very similar reasoning to why neural networks can be really great at classifying malware based on the program structure or doing semantic segmentation on well-defined scenes. > The team trained a second neural network to learn from 10 years of standard clinical patient data, 22 factors such as patients' age, weight, race, and prescription drug use. Again, this kind of multi-dimensional pattern-matching is pretty much much a machine learning wheelhouse. > [They] were validated in tests with an independent patient cohort from 60 health centers across the United States, with different cardiac histories and different imaging data And apparently has a bunch of independent validation. Neat stuff, I'm curious to see how it will develop/be distributed in the future. Disclosure: I recently accepted a job offer from JHU, albeit in a different field.
- emerged 5y ago
  I’m a bit more cynical, given Technology’s track record in all other industries. Using AI in medical contexts is quite frightening to me. I don’t think we think it through at the pace it moves.
  - qchris 5y ago
    I get the skepticism, truly--I actually wrote a couple articles about ethics and machine learning, and I completely agree there have definitely been cranks or bad actors using this kind of technology in both this space and many others. But if you were going to apply data science/machine learning to healthcare (personally, I dislike the term "AI"), I think that this project would be very close to both how and where you would want it. Peer-reviewed research with independent confirmation, in an narrow, image-based diagnosis, overseen by medical professionals throughout the process (not directly making recommendations to patients), by one of the world's leading medical research institutions. This isn't a catch-all, and it's certainly possible that cynicism could be warranted down the line. But for me, personally, I think that cautious optimism for this specific situation overrides the cynicism.
DantesKite 5y ago
This is the kind of medical progress I love to see.
mjmj 5y ago
My family has an unknown genetic variant that causes sudden cardiac death. We’ve been studied a lot. My father in law and his brother both died suddenly jn their early 50’s. My wife and brother in law both had elective heart surgery in their 30’s to install defibrillators as safety precautions to avoid suddenly dropping dead. Our two daughters both have unknown heart variants and one of them is on a beta blocker for life since the age of 1 to avoid sudden cardiac episodes. She’s also forbidden to drink stimulants or play certain sports for risk of heart episodes. She looks completely healthy and normal and wants to play as intense as other kids. This tech could mean that my children don’t have to face the same decision as their elders having to decide between dangerous and expensive surgeries for an unknown risk or living your life in fear. I can’t tell you how huge this is for us if regular checkups would be enough to say, yes go live and play, enjoy your life. Things look good.
mateo1 5y ago
In all of these cases the "AI" is assessing some features of the patient scans and history to reach it's conclusions. Why isn't the method ("algorithm") made clear and presented to actual human experts so they can incorporate it in their diagnostic routines? I'm sorry to be cynical, but all I've seen so far from "medical AI" is spurious correlational relationships in data, sometimes even in noise, presented as a causal deterministic predictions. If you found a new way of predicting cardiac arrest, that's great. Let us know how.

96 points by hhs 5y ago

I am absolutely clueless about heart medicine, but it seems like having monitoring of heartbeat in real-time should be able to predict potential anomalous and problems. I expect that Apple with watch will dramatically be able to save lives in the future with their products.

deleted 5y ago
[deleted]
agumonkey 5y ago
The few that I got is that cardiac electrophysiology is still mysterious and can derail in weird ways even if you look at it closely.
gleenn 5y ago
Apple is quick to tell you all the things that the heart monitor can NOT do, but I think they have already had cases where the watch detected peculiarities in heart rhythms and suggested getting things checked out by a doctor which did save lives. https://wccftech.com/apple-watch-saves-life-of-a-70-year-old-woman-with-afib-heart-condition/ https://wccftech.com/apple-watch-saves-life-of-a-70-year-old...
macintux 5y ago
I’m reminded of someone who insisted in a thread here that heart rate monitoring on Apple Watch was stupid because they could just check their own whenever they wanted to.
mjmj 5y ago
Yeah, That’s the dream and already happening as far as heart rhythm abnormalities. But wearables are pretty lacking. For example, I have a resting heart rate of 40bpm due to intense exercise. Iwatch won’t register heart rates that low, but if I get an EKG I’m fine. Additionally EKG’s puts leads all over your chest to get precise electrical measurements. A watch on your wrist isn’t going to be comparable, esp with things like sudden cardiac death. This article takes it even further as you need detailed imaging to really save these types of patients. Since we don’t yet know many of the underlying genetic variants or causes of sudden cardiac death. It’s more common than people realize and often goes undiagnosed or misdiagnosis because it’s hard to detect until too late. Source: Multiple people in my family have died from sudden cardiac death. All with perfectly normal EKG’s before they passed.

earleybird 5y ago

My very tangential observations in the cardiology domain is that it is in some respects a dark art that requires years, perhaps decades of experience to understand underlying mechanisms. While this certainly looks promising in a person / not person recognition kinda way; I'm hoping it can shed some insight the interaction between scarring and conductivity that leads to arrhythmias.

jrapdx3 5y ago
Your observation about practicing medicine being a "dark art" has a lot of merit. As such the idea applies to most if not all medical specialties and I strongly suspect is no less true among science-based disciplines in general. In health care domains we desperately want to believe providers know precisely what they're doing. It's particularly vexing to find out that "facts" are surrounded by an intrinsic level of uncertainty. IOW whatever action a practitioner deems best in a given situation is a judgement call grounded in experience. Sure, that's bolstered by underlying science, systematic investigations and published reports, but still there's no escaping the probabilistic nature of knowledge in the fields of medicine. The provider you want to have is one who strives to do what's possible up to the limits of techniques and technology, and above all seeks to learn from every patient encounter.
Smileyferret 5y ago
I don’t disagree with you that much of medicine is hand-waving and voodoo magic, but arrhythmias due to scar tissue likely have a similar mechanism to other well-studied arrhythmias. Overall I think that cardiology has some of the more scientific explanations of its pathophysiology than other fields. Scarring simply interrupts smooth conduction of impulses throughout the myocardium and makes it more susceptible to arrhythmias. If you want to see a similar mechanism explained, check out this video: https://youtu.be/j8pVU9snSH4 https://youtu.be/j8pVU9snSH4
- earleybird 5y ago
  Thanks for the link. I need to choose words better - rather than "dark arts" I probably should have said "tacit knowledge". I certainly didn't mean to imply that arrhythmias are not well studied, rather, my hope is that we can use AI methods to do better science. side note: I know EEs who claim antenna design is a black art :-) It also is well studied and yet according to some, it appears magical at times.

carbocation 5y ago

I haven't read the research article yet, but since the jhu.edu article doesn't link to it, here it is: https://www.nature.com/articles/s44161-022-00041-9 https://www.nature.com/articles/s44161-022-00041-9

donttellitsme 5y ago
Thanks for the link. Unfortunately it does not seem to be on sci-hub (yet?) and apparently my institution doesn't want to pay for nature anymore. While I have no doubt that imaging-based neural nets can outperform a lot of the cardiac risk scores in clinical use today (they are usually pretty rudimentary), I would be fairly cautious about this article. Let's say one of the authors has a pretty long record of making extraordinary claims backed by very little evidence; managing to impress the medical community while at the same time being regarded as an impostor in the computer science community. Of course I'm just a random stranger on the internet, so I might just be a jealous competitor ;)
- carbocation 5y ago
  I have a Harvard library login and ran into the same issue (tried sci-hub as well, no luck).

antihero 5y ago

Pretty cool and terrifying if they made it an app I guess

deleted 5y ago
[deleted]
Teknoman117 5y ago
I mean, it requires heart imaging, which you're not going to be getting without access to some very expensive equipment (assuming you just randomly wanted to look at this rather than getting images back from your doctor).

qchris 5y ago

I'm generally pretty skeptical of claims of applying machine learning to improve healthcare outcomes (they often seem to be a poorly thought-out veneer), but at first glance, this one actually seems pretty exciting. It also seems like it's more of a "machines aiding humans, not replacing them" situation which, especially in context of healthcare, is always nice to see. > Current clinical cardiac image analysis extracts only simple scar features like volume and mass, severely underutilizing what's demonstrated in this work to be critical data. > "The images carry critical information that doctors haven't been able to access," said first author Dan Popescu, a former Johns Hopkins doctoral student. This is, like, the thing that machine learning is really good at--pulling out additional information from complex patterns represented as imagery. It's a very similar reasoning to why neural networks can be really great at classifying malware based on the program structure or doing semantic segmentation on well-defined scenes. > The team trained a second neural network to learn from 10 years of standard clinical patient data, 22 factors such as patients' age, weight, race, and prescription drug use. Again, this kind of multi-dimensional pattern-matching is pretty much much a machine learning wheelhouse. > [They] were validated in tests with an independent patient cohort from 60 health centers across the United States, with different cardiac histories and different imaging data And apparently has a bunch of independent validation. Neat stuff, I'm curious to see how it will develop/be distributed in the future. Disclosure: I recently accepted a job offer from JHU, albeit in a different field.

emerged 5y ago
I’m a bit more cynical, given Technology’s track record in all other industries. Using AI in medical contexts is quite frightening to me. I don’t think we think it through at the pace it moves.
- qchris 5y ago
  I get the skepticism, truly--I actually wrote a couple articles about ethics and machine learning, and I completely agree there have definitely been cranks or bad actors using this kind of technology in both this space and many others. But if you were going to apply data science/machine learning to healthcare (personally, I dislike the term "AI"), I think that this project would be very close to both how and where you would want it. Peer-reviewed research with independent confirmation, in an narrow, image-based diagnosis, overseen by medical professionals throughout the process (not directly making recommendations to patients), by one of the world's leading medical research institutions. This isn't a catch-all, and it's certainly possible that cynicism could be warranted down the line. But for me, personally, I think that cautious optimism for this specific situation overrides the cynicism.

DantesKite 5y ago

This is the kind of medical progress I love to see.

mjmj 5y ago

My family has an unknown genetic variant that causes sudden cardiac death. We’ve been studied a lot. My father in law and his brother both died suddenly jn their early 50’s. My wife and brother in law both had elective heart surgery in their 30’s to install defibrillators as safety precautions to avoid suddenly dropping dead. Our two daughters both have unknown heart variants and one of them is on a beta blocker for life since the age of 1 to avoid sudden cardiac episodes. She’s also forbidden to drink stimulants or play certain sports for risk of heart episodes. She looks completely healthy and normal and wants to play as intense as other kids. This tech could mean that my children don’t have to face the same decision as their elders having to decide between dangerous and expensive surgeries for an unknown risk or living your life in fear. I can’t tell you how huge this is for us if regular checkups would be enough to say, yes go live and play, enjoy your life. Things look good.

mateo1 5y ago

In all of these cases the "AI" is assessing some features of the patient scans and history to reach it's conclusions. Why isn't the method ("algorithm") made clear and presented to actual human experts so they can incorporate it in their diagnostic routines? I'm sorry to be cynical, but all I've seen so far from "medical AI" is spurious correlational relationships in data, sometimes even in noise, presented as a causal deterministic predictions. If you found a new way of predicting cardiac arrest, that's great. Let us know how.