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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

#161

Post by prometheus76 »

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…

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

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

#162

Post by [deleted] »

uberwindung wrote: post #151

..”In this modelling study, we defined race as a social, political, and legal construct that relates to the interaction between external perceptions (ie, “how do others see me?”) and self-identification, and specifically make use of self-reported race of patients in all of our experiments.” Garbage research.

[deleted]

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

#163

Post by groby_b »

uberwindung wrote: post #151

..”In this modelling study, we defined race as a social, political, and legal construct that relates to the interaction between external perceptions (ie, “how do others see me?”) and self-identification, and specifically make use of self-reported race of patients in all of our experiments.” Garbage research.

And you are qualified to make that assessment because...?

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

#164

Post by ppqqrr »

So there’s material differences that supports certain prejudices; big surprise, turns out human societies have been (and still is) working very hard for thousands of years to craft those differences - isolating, separating, enslaving, oppressing, exiling their scapegoat “others”. The question is not whether the differences are real, but whether we can prevent AI from being used to perpetuate those differences. TBH, we don’t stand a chance; we live in a society where most people cannot even wrap their heads around why it shouldn’t perpetuate those differences.

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

#165

Post by nradov »

codefreeordie wrote: post #71
aulin wrote: post #58

Earlier quoted context omitted.

ok, maybe it's an US specific thing, why wouldn't a clinical radiologist have all the information he can gather about his patient including race to help the diagnosis?

Because in the US we are required to pretend that there is no such thing as race and no such thing as gender, and all people are exactly and precisely the same and there can be no differences.

Actually, the US federal government specifically recommends that healthcare providers record patients' race, ethnicity, assigned sex, and gender identity. Most of those elements are self identified.

https://www.healthit.gov/isa/uscdi-data-class/patient-demogr...

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

#166

Post by axg11 »

colinmhayes wrote: post #160
axg11 wrote: post #152

Earlier quoted context omitted.

Perfect example of citations-driven research. The authors aren’t motivated by a genuinely interesting scientific question (“are anatomical differences between genetically distinct groups of people visible in X-rays?”). Instead, the authors know that training a classifier to predict race will generate controversial headlines and tweets. All publicity, positive or negative, leads to more citations.

> 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 distinct.

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

#167

Post by sudosysgen »

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 it's trivial, why are results so variable on different ethnicity websites? And what happens when the definition of "white" changes in 30 years to unambiguously include Latinos?

(Hint : what you want is a classifier on ethnicity, and those aren't trivial either)

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

#168

Post by sudosysgen »

uberwindung wrote: post #151

..”In this modelling study, we defined race as a social, political, and legal construct that relates to the interaction between external perceptions (ie, “how do others see me?”) and self-identification, and specifically make use of self-reported race of patients in all of our experiments.” Garbage research.

This is the only reasonable possible way to do it. Races are fluid and ill-defined constructs, so self-identification is the best you can do for ground truth.

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

#169

Post by nojito »

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…

There’s nothing trivial about determining race in healthcare research.

Feel free to cite sources.

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

#170

Post by AlotOfReading »

inglor_cz wrote: post #21
mensetmanusman wrote: post #4

What does this mean in terms of race being a social construct/concept?

Ever more complicated attempts to bridge the gap by muddying the waters. Frankly, even a freshly arrived alien from Mars or Titan could easily tell Icelanders, Mongols and Xhosa apart, without knowing anything about our culture. The fact that there has been a lot of interbreeding/admixture since the Age of Sail began, does not mean that there aren't meaningful biological differences between the original groups, which…

One of the major issues with biological race realism is that common race classifications do not form monophyletic groupings. If you already have a set of definitions you need to fit, any sufficiently large set of features can trivially classify those categories. It doesn't matter if the groups are race or "people who like licorice". When the features and population sizes aren't uniformly distributed, you can even get very strong correlations, without there being a meaningful underlying basis.

The social definition is used because that's a most scientifically meaningful and useful definition that avoids many of the issues with biological race realism.

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