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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

#31

Post by nerdponx »

hellohowareu wrote: post #5

Simply go to google image and search: "skeletal racial differences". subspecies are found across species-- they happen based on geographic dispersion and geographic isolation, which humans underwent for tens and hundreds of thousands of years. Welcome to the sciences of anatomy, anthropology, and forensics. other differences: - slow twitch vs fast twitch muscle - teeth shape - shapes and colors of various parts - gen…

Then problem is that human experts sometimes can't tell the difference while the model can.

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

#32

Post by _8j50 »

mensetmanusman wrote: post #4

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

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 black and white based on skin color are as well, indians and east asians are also one "race".

Ethnicities are not social constructs but race is. The AI finds ethnic differences and correlates them with self-percievied social/racial classification.

"Race" as the evil social construct it is, takes ethnic differences and intrprets them to mean some ethnicities are different races of humans than others as in not just different ancestors but differently created or evolved despite all evidence and major religion saying all humans are one species (homosapiens) that have a common homosapien ancestor.

I thought all this was obvious but the social climate recently is very weird.

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

#33

Post by [deleted] »

aulin wrote: post #18
tech-historian wrote: post #2

The interpretation part hit home: "The results from our study emphasise that the ability of AI deep learning models to predict self-reported race is itself not the issue of importance. However, our finding that AI can accurately predict self-reported race, even from corrupted, cropped, and noised medical images, often when clinical experts cannot, creates an enormous risk for all model deployments in medical imaging.…

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?

[deleted]

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

#34

Post by SpicyLemonZest »

civilized wrote: post #19

It would be nice to see more genuine, enthusiastic scientific curiosity to understand how the ML algorithms are doing this, rather than just abject terror and alarm.

It seems like the reason the researchers in this paper are concerned is precisely that they tried and failed to understand how the ML algorithms are doing this. If they’d discovered that white people have a subtly distinctive vertebra shape the model was detecting, it would have been much more of “oh, we discovered a neat fact”.

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

#35

Post by redox99 »

bb123 wrote: post #10

One idea is that there is some difference in the x-rays themselves that could potentially be explained by racial disparities in access to (and quality of) healthcare. Maybe white people tend to visit hospitals with newer, better equipment or better trained radiographers and the model is picking up on differences in the exposures from that.

These results seem too accurate to be explained only by a correlation to the medical equipment used.

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

#36

Post by jcranberry »

airza wrote: post #27
hellohowareu wrote: post #5

Simply go to google image and search: "skeletal racial differences". subspecies are found across species-- they happen based on geographic dispersion and geographic isolation, which humans underwent for tens and hundreds of thousands of years. Welcome to the sciences of anatomy, anthropology, and forensics. other differences: - slow twitch vs fast twitch muscle - teeth shape - shapes and colors of various parts - gen…

The article is pretty fascinating and I recommend that you actually read it. For example: >"We found that deep learning models effectively predicted patient race even when the bone density information was removed for both MXR (AUC value for Black patients: 0·960 [CI 0·958–0·963]) and CXP (AUC value for Black patients: 0·945 [CI 0·94–0·949]) datasets. The average pixel thresholds for different tissues did not produce…

So just from the silhouette of a skeleton, if I understand that correctly?

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

#38

Post by dijit »

PartiallyTyped wrote: post #20
dijit wrote: post #6

Earlier quoted context omitted.

Race, in terms of physiology has never been regarded by science to be a social construct. In fact it can be medically harmful to think this way.

One of the reasons certain communities were hit harder with Covid was vit D deficiency as a consequence of skin color.

That is one hypothesised cause for the disparity, social factors in those cases need to be controlled for.

A better discussion is around sickle cell anaemia[0] which is exclusively carried by people of African or Afro-Caribbean descent.

[0]: https://en.wikipedia.org/wiki/Sickle_cell_disease

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

#39

Post by sim7c00 »

aulin wrote: post #18
tech-historian wrote: post #2

The interpretation part hit home: "The results from our study emphasise that the ability of AI deep learning models to predict self-reported race is itself not the issue of importance. However, our finding that AI can accurately predict self-reported race, even from corrupted, cropped, and noised medical images, often when clinical experts cannot, creates an enormous risk for all model deployments in medical imaging.…

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?

soon they will want to remove race indicators for photographs and tik tok videos. who knows, maybe its racist to be of a race >.>

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

#40

Post by wutbrodo »

dijit wrote: post #6
mensetmanusman wrote: post #4

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

Race, in terms of physiology has never been regarded by science to be a social construct. In fact it can be medically harmful to think this way.

Unfortunately, that's not quite true. Here's the AMA[1] with a press release entitled "New AMA policies recognize race as a social, not biological, construct".

They discourage using race as a source of any physiological signal. They do allow using genetics, but the relevant situations are the many many ones where genetic testing isn't possible or doesn't yet provide useful signal.

Unaccountable institutions get captured very easily, and the race cult that's swept through our educated class has been a very powerful one.

[1] https://www.ama-assn.org/press-center/press-releases/new-ama...

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