[xattt]

Yes, but with machine learning this time!

> This approach represents an automated and accessible screening strategy for LV systolic dysfunction, particularly in low-resource settings.

If the low-resource setting means there is no one to interpret a 12-lead that suggests LV dysfunction, what are the chances the individual will have reliable access to an echo or, further down the line, an ACEi to slow remodelling?

[csdvrx]

> If the low-resource setting means there is no one to interpret a 12-lead that suggests LV dysfunction, what are the chances the individual will have reliable access to an echo or, further down the line, an ACEi to slow remodelling?

Why would a human be needed to interpret anything, if the detection can be done by software?

It may be legally required, but that can change with the stroke of a pen.

As for getting access to an echo, why wouldn't it be possible to also have that done by software?

Then for ACEi, if people already can easily purchase illegal drugs, why do you think they won't be able to buy ACI?

In a "low resource setting", I think enforcing drug laws may also be affected by the "low resources": people who want to avoid heart problems may be strongly incentivized to disregard the already poorly enforced laws to acquire whatever they need thay may increase their lifespan.

[haldujai]

> Why would a human be needed to interpret anything, if the detection can be done by software?

ECG machines already do this based on the electrical signal data rather than using a picture of the ECG.

> As for getting access to an echo, why wouldn't it be possible to also have that done by software?

You need an ultrasound machine which at the very least is a point of care model (~$1-2000) as well as an operator competent in acquiring the images. Ironically if you have one of these the software already exists to do what this model is doing with higher accuracy and provides substantially more information.

> Then for ACEi, if people already can easily purchase illegal drugs, why do you think they won't be able to buy ACI?

I can't imagine a location having a healthcare provider, ultrasound machine and ACEI accessible while still using an ECG machine obsolete enough to require this.

[csdvrx]

Using pictures instead of signals, allowing to do automation with existing (or obsolete) tools, is a true innovation IMHO.

> I can't imagine a location having a healthcare provider, ultrasound machine and ACEI accessible while still using an ECG machine obsolete enough to require this.

I can imagine many locations having no healthcare provider (or maybe just a nurse) and people putting a vest/belt/whatever whose electrodes are hooked to an obsolete machine, to get a quick estimations of their risk, using special software running on their smartphone to interpret the pictures.

Updating software running on the machine would be hard and risky.

[haldujai]

> Using pictures instead of signals, allowing to do automation with existing (or obsolete) tools, is a true innovation IMHO.

> I can imagine many locations having no healthcare provider (or maybe just a nurse) and people putting a vest/belt/whatever whose electrodes are hooked to an obsolete machine, to get a quick estimations of their risk, using special software running on their smartphone to interpret the pictures.

So the innovation is that: A low-resource location with no medical expertise (and again is using a 20 year old ECG machine that's somehow still functional) is going to be able to jerry-rig a vest (noting that 12 leads require accurate placement) and then is going to take a picture of the resultant ECG with a smart phone and use a model that's not been validated on an average risk person or noisy ECG data to analyze said picture?

Or we can keep it simple and just use a $50 single lead ECG that plugs into a smart phone and/or is already incorporated into wearables requiring zero medical expertise for accurate use.

https://www.medrxiv.org/content/medrxiv/early/2022/12/04/202...

> to get a quick estimations of their risk

This is my point about not understanding medical relevance.

Phenomenal, you know that you have a risk of left ventricular systolic dysfunction. Now what? What's the next step? Where are you going to get the echo or medical professional?

> Updating software running on the machine would be hard and risky.

You don't have to update the software, you just have to use a machine from the 2000s.

[csdvrx]

> Phenomenal, you know that you have a risk of left ventricular systolic dysfunction. Now what? What's the next step? Where are you going to get the echo or medical professional?

You don't understand, because you keep assuming echo or medical professionals will be needed, to keep doing what is now medically relevant.

If the same tweaks can be done at the next step (automating readings from obsolete machines, say by recognizing some heart landmarks to align and measure doppler flows purely though software) yes, the end result is still an "intervention" ("take this pill")

But if everything leading to that intervention can be optimized, or even large parts of it money will be saved.

The current approach is not set in stone: this new approach could help those who have no healthcare professional, can't even pay for the extras (modern EKG, confirmation by echo etc) but can pay for basic EKG + ACEi if needed.

These same person which could get nothing in the current approach could at least be better treated

[haldujai]

> You don't understand, because you keep assuming echo or medical professionals will be needed, to keep doing what is now medically relevant.

Yes, I believe in the laws of physics which state what you are describing is impossible.

> say by recognizing some heart landmarks to align and measure doppler flows purely though software

No amount of AI will change the fact that you cannot derive volumetric information from the electrical rhythms of the heart. You cannot obtain doppler or volumetric flow information from an ECG, you need ultrasound (i.e. an echo).

This model is almost certainly learning that certain ECG waveform changes reflective of other diseases and physiological changes place you at higher risk of LVSD. We've known these relationships from the 1990s, probably earlier.

> The current approach is not set in stone: this new approach could help those who have no healthcare professional, can't even pay for the extras (modern EKG)

If you live in a developed country there is no such thing as modern vs old EKG. I would strongly wager the same holds true in most developing countries as these older machines are unlikely to still be functional.

> (confirmation by echo etc) but can pay for basic EKG + ACEi if needed.

There are multiple causes of LVSD. They have different treatments.

[uj8efdjkfdshf]

I should point out that ECG machines that use heuristics to provide on the spot diagnoses already exist, are widespread and are way easier to implement.

[0] https://www.nejm.org/doi/full/10.1056/NEJM199112193252503

[haldujai]

So what they're doing here is using deep learning on pictures of ECGs instead of the electrical signals used by machines that provide heuristics.

The proposed use case/workflow seems to be that (somehow) someone, somewhere is using an ECG machine that doesn't provide an automatic preliminary interpretation (i.e. > 20 years old) that is (somehow) still operational and the operator doesn't know how to interpret an ECG. They would then presumably upload a picture of the ECG to a platform that can run a deep learning model on the image. This is also apparently happening in a place where a clinician is then available and echo (for confirmation, quantitative EF and etiology) as well as medications are still accessible to impact patient management/outcomes.

This reads like something done by pure CS folks who don't understand how medicine works but the authors include cardiologists.

Ignoring the glaring validity issues of a study population that only included patients who had an indication for echo, the only explanation I can see for why someone would do this is to puff up the author's h-index as this will undoubtedly be cited in several "emerging applications of AI in medicine" papers.