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I let ChatGPT analyze a decade of my Apple Watch data, then I called my doctor

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Re: I let ChatGPT analyze a decade of my Apple Watch data, then I called my doctor

#221

Post by inopinatus »

FeteCommuniste wrote: post #124
inopinatus wrote: post #100

Earlier quoted context omitted.

Many of those metrics are population or sampling measures and are confounded by many factors at an individual level. The most notorious of which is BMI; it is practically a category error to infer someone's health or risk by individual BMI, and yet doing so remains widespread amongst people that are supposed to know better. Instrumentation and testing become primarily useful at an individual level to explain or inves…

> The most notorious of which is BMI; it is practically a category error to infer someone's health or risk by individual BMI, and yet doing so remains widespread amongst people that are supposed to know better. BMI works fine for people who aren't very muscular, which is the great majority of people. Waist to height ratio might be more informative for people with higher muscle mass.

> BMI works fine

An individual learns nothing from its calculation and it has no clinical value. I receive more constructive feedback from an auntie jabbing me in the chest and saying "you got fat".

> the great majority of people

There is wide morphological variety across human populations, so, no.

Re: I let ChatGPT analyze a decade of my Apple Watch data, then I called my doctor

#222

Post by saghm »

chrisfosterelli wrote: post #20

Health metrics are absolutely tarnished by a lack of proper context. Unsurprisingly, it turns out that you can't reliably take a concept as broad as health and reduce it to a number. We see the same arguments over and over with body fat percentages, vo2 max estimates, BMI, lactate thresholds, resting heart rate, HRV, and more. These are all useful metrics, but it's important to consider them in the proper context tha…

On the other hand, if compressing to a single number is not possible, a doctor will just refuse to give a grade in that way. In my experience, most doctors tend to be very careful about trying to avoid saying anything definitive that they're not actually sure of, even if they're reasonably confident, in large part because part of their job involves understanding how patients react to how things are communicated to them. Being willing to confidently give a misleading answer to a bad question is itself as bad thing when it comes to health data because regular people aren't able to (and shouldn't be expected to) figure out what various interferences from health data happen to feasible from a given data set.

Re: I let ChatGPT analyze a decade of my Apple Watch data, then I called my doctor

#223

Post by teleforce »

chrisfosterelli wrote: post #20

Health metrics are absolutely tarnished by a lack of proper context. Unsurprisingly, it turns out that you can't reliably take a concept as broad as health and reduce it to a number. We see the same arguments over and over with body fat percentages, vo2 max estimates, BMI, lactate thresholds, resting heart rate, HRV, and more. These are all useful metrics, but it's important to consider them in the proper context tha…

>But a doctor who sees a person come in who isn't complaining about anything in particular, moves around fine, doesn't have risk factors like age or family history, and has good metrics on a blood test is probably going to say they're in fine cardio health regardless of what their wearable says.

The standard risk model for CVD based on SCORE-2 and PREVENT like parameters are very poor as reported in the recently published paper on the their accuracy performance by the Swedish team [1]. As all CVD risk stratification with cardiologist review, the most important accuracy is sensivity (avoiding false negative that will escape review) of SCORE-2 and PREVENT, 48% and 26%, respectively.

The paper alternative proposal increased the sensitivity to 58% by performing clustering instead of conventional regression models as practiced in the standard SCORE-2 (Europe) and PREVENT (US).

These type of models including the latest proposal performed very poorly as indicated by their otherwise excellent and intuitive display of graphical abstract results [1].

[1] Risk stratification for cardiovascular disease: a comparative analysis of cluster analysis and traditional prediction models:

https://academic.oup.com/eurjpc/advance-article/doi/10.1093/...

Re: I let ChatGPT analyze a decade of my Apple Watch data, then I called my doctor

#224

Post by danielmarkbruce »

Someone wrote: post #102
cameldrv wrote: post #69

I dunno, if the Apple Watch said he had a vo2max of 30, that probably means he can’t run a mile in less than 12 minutes or so. He’s probably not at all healthy…

> he had a vo2max of 30, that probably means he can’t run a mile in less than 12 minutes or so. He’s probably not at all healthy… Health and fitness correlate but are different things. VO2max is more about fitness than about health. Also, looking at https://en.wikipedia.org/wiki/VO2_max#Reference_values , 30 is about average for men in their 40s/50s, which, form a quick google, I estimate is the author’s age range.

This is a silly take. VO2 max is one of the strongest predictors of all cause mortality. Various large scale studies have shown it to be true.

Re: I let ChatGPT analyze a decade of my Apple Watch data, then I called my doctor

#225

Post by danielmarkbruce »

dgxyz wrote: post #110
cameldrv wrote: post #69

I dunno, if the Apple Watch said he had a vo2max of 30, that probably means he can’t run a mile in less than 12 minutes or so. He’s probably not at all healthy…

If Apple watch said anything about that it's probably wrong. It can't accurately measure VO2 max. Incidentally I got rid of mine recently. It is bliss not having one. Also VO2 max is a crappy measure of fitness. I apparently had "average" VO2 max after a treadmill test. I can hike 50km with a 2km elevation gain in one go and not die. People with higher VO2 max I know, dropped out.

vo2 max is one of the strongest predictors of all cause mortality.

Re: I let ChatGPT analyze a decade of my Apple Watch data, then I called my doctor

#226

Post by danielmarkbruce »

vo2 max is one of the strongest predictors of all cause mortality. It's been reproduced across several large scale studies. I'm on the side of ChatGPT on this one. I'd guess the writer of this article is leaving something out.

A family member recently passed away from a rare, clinically diagnosed disease. ChatGPT knew what it was a couple months before the relevant specialists diagnosed it.

Re: I let ChatGPT analyze a decade of my Apple Watch data, then I called my doctor

#227

Post by adastra22 »

ignoramous wrote: post #25
brandonb wrote: post #8

Earlier quoted context omitted.

FWIW, Apple has published validation data showing the Apple Watch's estimate is within 1.2 ml/kg/min of a lab-measured Vo2Max. Behind the scenes, it's using a pretty cool algorithm that combines deep learning with physiological ODEs: https://www.empirical.health/blog/how-apple-watch-cardio-fit...

The paper itself: https://www.apple.com/healthcare/docs/site/Using_Apple_Watch... Seems like Apple's 95% accuracy estimate for VO2 max holds up. Thirty participants wore an Apple Watch for 5-10 days to generate a VO2 max estimate. Subsequently, they underwent a maximal exercise treadmill test in accordance with the modified Åstrand protocol. The agreement between measurements from Apple Watch and indirect calorimetry…

That is an extraordinary small sample size.

Re: I let ChatGPT analyze a decade of my Apple Watch data, then I called my doctor

#228

Post by lurking_swe »

dgxyz wrote: post #110
cameldrv wrote: post #69

I dunno, if the Apple Watch said he had a vo2max of 30, that probably means he can’t run a mile in less than 12 minutes or so. He’s probably not at all healthy…

If Apple watch said anything about that it's probably wrong. It can't accurately measure VO2 max. Incidentally I got rid of mine recently. It is bliss not having one. Also VO2 max is a crappy measure of fitness. I apparently had "average" VO2 max after a treadmill test. I can hike 50km with a 2km elevation gain in one go and not die. People with higher VO2 max I know, dropped out.

You’re not wrong. However - the Health app on the iphone (where you can view your health data) makes this VERY clear. Most people just don’t read.

I’ll quote:

“This is a measurement of your VO2 max, which is the maximum amount of oxygen your body can consume during exercise. Also called cardiorespiratory fitness, this is a useful measurement for everyone from the very fit to those managing illness.

A higher VO, max indicates a higher level of cardio fitness and endurance.

Measuring VO2 max requires a physical test and special equipment. You can also get an estimated VO, max with heart rate and motion data from a fitness tracker. Apple Watch can record an estimated VO max when you do a brisk walk, hike, or run outdoors.

VO, max is classified for users 20 and older. Most people can improve their VO, max with more intense and more frequent cardiovascular exercise. Certain conditions or medications that limit your heart rate may cause an overestimation of your VO, max. VOz max is not validated for pregnant users. You can indicate you're taking certain medications or add a current pregnancy in Health Details.”

Re: I let ChatGPT analyze a decade of my Apple Watch data, then I called my doctor

#229

Post by Deklomalo »

elzbardico wrote: post #199
Deklomalo wrote: post #132

Earlier quoted context omitted.

You state a lot of things without testing it first? A LLM has structures in its latent space which allows it to do basic math, it has also seen enough data that it has probably structures in it to detect basic trends. A LLM doesn't just generate a stream of tokens. It generates an embedding and searches/does something in its latent space, then returns tokens. And you don't even know at all what LLM Interfaces do in t…

That's not how it works.

What exactly?

Here is the paper were I read about it: https://arxiv.org/html/2601.04480v1

Re: I let ChatGPT analyze a decade of my Apple Watch data, then I called my doctor

#230

Post by haldujai »

theshrike79 wrote: post #96
haldujai wrote: post #37

Earlier quoted context omitted.

How so?

ChatGPT will actually look at your whole medical history, listen to you, think and check multiple different options before making a decision. You can spend hours chatting with it back and forth. An average human doctor has maybe 15 minutes allotted to getting to know you, analyse and determine a course of action. Which is usually "take some ibuprofen and let's see if it goes away". Then you go again in two weeks with…

I wonder if in your case (which is very common) the issue is a mismatch between expectations and reality. The medical system as we know is not designed for someone to listen to you and do a back and forth for hours. If we did that we would only treat 2-4 patients a day. It’s also not particularly helpful.

Time spent in a medical encounter is tied to patient satisfaction but there is rapid drop off for clinical benefit especially in the current day where investigations are more important than a physical exam in most cases and more than history in a substantial portion.

15 minutes is what we book as follow-ups or minor assessments in US+Canada, usually sufficient for most things. New consults or complex patients are 30-60 minutes.

Infodumping is not particularly helpful. Doctors are trained to use a combination of open and closed questions to guide the encounter based on their thinking and understanding of medicine. It’s relevant past medical history as not every symptom or past disease is necessarily useful in assessing what’s wrong today.

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