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AI recognition of patient race in medical imaging: a modelling study

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Re: AI recognition of patient race in medical imaging: a modelling study

#171

Post by wahern »

nerdponx wrote: post #155
codefreeordie wrote: post #106

Earlier quoted context omitted.

It sometimes makes sense to scrub race/ethnicity/gender information from certain types of data, typically when a human is going to be making individual decisions. For example, not having race data on resumes is generally productive, because that categorization can't provide a meaningful input to the decision associated with an individual person. Even if it were to be the case that there was some correlation between r…

Then you should be looking at ethnicity and not "race" as such. For example, Ashkenazi Jews as an ethnic group are genetically very distinct from other Europeans, but are generally considered "white" on self-reported race surveys.

"Very distinct" seems a little exaggerated. Compare the "Autosomal genetic distances" between Ashkenazi jews and other European groups at https://en.wikipedia.org/wiki/Genetic_studies_on_Jews with a similar table of Intra-European distances at https://en.wikipedia.org/wiki/Fixation_index. Finns and French have like twice the distance as Italians and Ashkenazi.

Now look just above that latter table, showing distances between East Asians and Europeans. The distances are far greater--more than 10x.

The precision with which we can identify and track ancestry, often based on small fractions of DNA (Y-chromosome in particular wrt Ashkenazi Jews, not mtDNA as one might think) doesn't imply the degree of genetic distinctiveness.

Re: AI recognition of patient race in medical imaging: a modelling study

#172

Post by _8j50 »

fullstackchris wrote: post #78
_8j50 wrote: post #32

Earlier quoted context omitted.

Still is? The AI is correlating biological features with self reported race. There are biological differences between people who have different ancestors. Finns are different from brits. The spanish are different from russians. Nigerians look different than somalians. The Japanese look differnet than filipinos. Race picks specific and arbitrary differences , for example hispanic is a different race in US society but…

Race as an entire concept to me has always been stupid at best. Sure, there are vast swaths of biological similarities (typically, though not necessarily) according to general geographic regions of the globe, but the real mistake was trying to give this vague concept a label. Can anybody give a definition of what "white" or "black" REALLY means? It's an impossible task. If we're talking just visually about skin color…

To me it is the epitome of laziness. The ultimate expression of the banality of evil.

Similar to prejudice and stereotyping or the worst of lies there is some truth in its reasoning but the untrue part, the lazy part allows people to commit evil and be unjust. A reason to harm others with minimal conscious discomfort.

Re: AI recognition of patient race in medical imaging: a modelling study

#173

Post by iancmceachern »

matthewdgreen wrote: post #42
aulin wrote: post #18

Earlier quoted context omitted.

what's this enormous risk they're talking about? racial bias in x-ray reading? race can be a risk factor in plenty of diseases, why should we actively try to remove this information from medical images?

"This issue creates an enormous risk for all model deployments in medical imaging: if an AI model relies on its ability to detect racial identity to make medical decisions, but in doing so produced race-specific errors, clinical radiologists (who do not typically have access to racial demographic information) would not be able to tell, thereby possibly leading to errors in health-care decision processes."

Interesting, this is like the dog learning calculus thing. We may create an AI that could perceive things that we aren't able to, or perceive things differently, because we're "limited" in a way that the AI isn't. We wouldn't be able to even tell this is going on, because we don't have the mental model in place to account for it to understand it. We'd be the dog.

Re: AI recognition of patient race in medical imaging: a modelling study

#174

Post by TMWNN »

nerdponx wrote: post #154
nerdponx wrote: post #43

Earlier quoted context omitted.

I suspect this is a "tank vs sky" problem. The article says that the bright areas of bone are not the most important for predicting race. What if it's some features of different hospitals and x-ray setups? Also did they release their code and anonymized data? If not, it's impossible to tell if this is a bug. If I got this result in my work, I would check it 10k times over because it defies belief. Even allowing subtl…

Replying to my own post because I can't edit it anymore. Apparently this is a known and persistent affect across a variety of other medical images, tests, and scans. Not just for a "race" but for ethnic groups in general, as well as biological sex. So this might actually just be an "AI hit piece" that otherwise confirms an unpalatable but persistent and strong effect in the literature. The causes seem to be badly und…

>This result is tremendously implausible to me, but I am finding quite a few articles documenting similar phenomena across things like retina scans and brain MRIs.

As prometheus76 says, perhaps you will one of these days be able to mentally resolve the inherent contradiction in the above sentence.

Re: AI recognition of patient race in medical imaging: a modelling study

#175

Post by HKH2 »

ibejoeb wrote: post #137
HKH2 wrote: post #132

Earlier quoted context omitted.

What term are you going to use instead? Subspecies? Breed?

I don't know. My hunch is that these suggestions, though, will be received poorly.

So your solution to people arguing in bad faith is to be so wordy that they give up and move onto more easily mischaracterized targets?

Re: AI recognition of patient race in medical imaging: a modelling study

#176

Post by cameldrv »

towaway15463 wrote: post #111
cameldrv wrote: post #109

Earlier quoted context omitted.

Well one thing you wouldn’t want to do is take the output of this model and then apply a correction factor for race on top of it, because the model is already taking that into account.

Is that true or would it help as a tie breaker in cases where the confidence was just at or below the threshold?

Well I suppose you only care about a correction factor to a binary model when it breaks a tie. You wouldn't want to apply a tiebreaker correction twice though.

Re: AI recognition of patient race in medical imaging: a modelling study

#177

Post by Ekaros »

axg11 wrote: post #166
colinmhayes wrote: post #160

Earlier quoted context omitted.

> genetically distinct groups of people Is race a genetically distinct marker though? I guess if you limit the sample enough it is, but I've always thought of race as more of a continuous quality than a distinct one.

Race _is_ a spectrum but genetic differences themselves are distinct (SNPs). It's trivial to train a classifier to distinguish race from genetic data, hence, I'd argue they are distinct groups. You can draw an analogy to colours in the rainbow: a rainbow is a spectrum but we can still draw lines that demarcate colours. Colour definitions are fuzzy at the edges but this doesn't mean coarse colour labels are not distin…

If we look at many many other mammals it is very clear that there is breeds. And those breeds are noticeably different, just think of cats, dogs, cows, pigs and so on. I really see no reason why this wouldn't extend to humans as well. And that the distinct groups wouldn't have some markers. Like longer than average bones.

Now, issue really is that whole race grouping is extremely murky. And not really anywhere specific enough as used in common speech. White, Black, Asian etc. are way too wide to be very useful. Even inside what we could understand as rather homogenous groups there is lot of difference between areas.

Re: AI recognition of patient race in medical imaging: a modelling study

#178

Post by nerdponx »

TMWNN wrote: post #174
nerdponx wrote: post #154

Earlier quoted context omitted.

Replying to my own post because I can't edit it anymore. Apparently this is a known and persistent affect across a variety of other medical images, tests, and scans. Not just for a "race" but for ethnic groups in general, as well as biological sex. So this might actually just be an "AI hit piece" that otherwise confirms an unpalatable but persistent and strong effect in the literature. The causes seem to be badly und…

>This result is tremendously implausible to me, but I am finding quite a few articles documenting similar phenomena across things like retina scans and brain MRIs. As prometheus76 says, perhaps you will one of these days be able to mentally resolve the inherent contradiction in the above sentence.

What is the value of being a smug jerk, especially if you plan to be wrong?

If your prior belief points strongly in one direction, it is completely rational to require strong weight of evidence in order to update it to point to the other direction.

And yes, it's a completely reasonable prior belief for a person who is not already versed in medical imaging literature.

I often find that people who study this literature have bad attitudes like yours. You should be grateful that there are people out there who value intellectual honesty enough to acknowledge when a result is a result and to change their beliefs. Instead I get two different people showing up to insult me.

Re: AI recognition of patient race in medical imaging: a modelling study

#179

Post by nerdponx »

prometheus76 wrote: post #161
nerdponx wrote: post #154

Earlier quoted context omitted.

Replying to my own post because I can't edit it anymore. Apparently this is a known and persistent affect across a variety of other medical images, tests, and scans. Not just for a "race" but for ethnic groups in general, as well as biological sex. So this might actually just be an "AI hit piece" that otherwise confirms an unpalatable but persistent and strong effect in the literature. The causes seem to be badly und…

What you are experiencing is cognitive dissonance. Take your time. It's never fun.

I don't see the value in insulting people about this. I wrote a longer response here: https://news.ycombinator.com/item?id=31421346 but it applies equally well to your post.

Re: AI recognition of patient race in medical imaging: a modelling study

#180

Post by croes »

gus_massa wrote: post #156
dang wrote: post #120

The submitted title ("AI identifies race from xray, researchers don't know how") broke the site guidelines by editorializing. Submitters: please don't do that - it eventually causes your account to lose submission privileges. From the guidelines ( https://news.ycombinator.com/newsguidelines.html ): " Please use the original title, unless it is misleading or linkbait; don't editorialize. "

It's the title of the Vice article about the same topic. https://www.vice.com/en/article/wx5ypb/ai-can-guess-your-rac... (It was posted last year.) (No idea why the OP used one title and another URL.) (The title of Vice is a bad title anyway.)

This or similar is the title on multiple sites.

https://www.boston.com/news/health/2022/05/18/scientists-cre...

https://nationalpost.com/health/health-and-wellness/ai-can-t...

https://www.sciencealert.com/ai-can-predict-people-s-race-fr...

https://www.iflscience.com/technology/ai-can-identify-race-f...

https://www.bostonglobe.com/2022/05/13/business/mit-harvard-...

Just a small collection

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