While we "focus on medical" clinical research isn't just testing new drugs, it's determining if one diet is better than other, it's finding prevention mechanisms and much much more. We work with any center that is running any type of research. And while we focus mostly on cancer treatments (70% of research dollars are spent here) we're building technology and want to expand to cover all types of clinical research as we grow.
(1) Identify various medications that are most likely to be effective between the different races
or
(2) Identify the differences between the races that is causing various medications to not be effective
If I ever figure out which would be better I'll let you know! Or if someone else chimes in.
For research done by private institutions (Pharma, Biotech, etc.) there is no mandate and it's on the researcher to make it a thing.
There's many ways you can rephrase it and still be correct, mind you.
If you're no longer country's minority, you cannot be majority-minority.
You might be hang up on the additional narrative attached to the word “minority”. Consider using “underpriviledged ethnic group", as a. not even today all ethnic groups are equal and b. it is entirely possible some other ethnic group to raise to demographic majority status, and still exhibit the socioeconomic characteristics of a poor population.
>You might be hang up on the additional narrative attached to the word “minority”.
You can't separate words from their "additional narratives" and expect all people to understand what you're attempting to convey. The context and connotation around words is absolutely necessary for communication, and to eschew it leads to poorer communication.
It's important to match the demographics of the population with the demographics of trial users. It's important to prevent as many deaths as we can.
It's important to account for differences between groups when you're developing healthcare.
But please, don't mangle mathematical terms.
You have just demonstrated what is called "attribution of intention" (as in you attributed an intention to the other person), which is a good indicator of a conversation going south.
(More general bias is "attribution bias")
HN guideline:
>Please respond to the strongest plausible interpretation of what someone says, not a weaker one that's easier to criticize. Assume good faith.
Do you have any thoughts on how improvements in these sorts of machine learning algorithms could make clinical trials more fair? I ask because you specifically mention that HDP uses AI in the article.
What we are also working on to make things more fair is helping open critical clinical trials in areas where there is a higher density of minority populations, as well as using demographic data in identifying where minority patients exist that match up to the latest clinical trials to prove to pharma companies that opening them in those areas is not only a moral improvement, but a financial one as well. (Disclaimer we do all of this de-identified).
Would definitely be great to have a larger discussion on this topic!
I'm not in the health field, so I don't know where the regulations stand, but I recall talking to someone who was advocating for this a couple of decades ago to avoid future cases like Thalidomide.
Would a drug proven effective for whites and ineffective for blacks in the US suddenly become effective for blacks and ineffective for whites if administered in Zimbabwe?
Or do you mean "minorities" in the "there are too many minorities in my waterpark" sense?