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A 13-year-old used my artificial nose to diagnose pneumonia

blog.benjamin-cabe.com

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Re: A 13-year-old used my artificial nose to diagnose pneumonia

#181

Post by russellbeattie »

dekhn wrote: post #176
russellbeattie wrote: post #167

Earlier quoted context omitted.

My son, now a sophomore at UCSC, definitely gave me a few moments of "Uhh... I really hope my kid isn't an idiot" at that age. Living in Silicon Valley, he had friends creating crazy Gary's Mod levels using Python (this was a decade ago) that they collaborated on using GitHub. I was shocked at how sophisticated junior high coders could get! My son, however, is not a techie and like his father, has always been a littl…

a high end high school will have a biology teacher who can teach high school students to do crispr (crispr is quite easy). My path into biology was looking into a microscope and seeing a world of non-computer state machines that behaved like cellular automata. and then my path led back to computers because real biology is much harder than CS. And I think some kids get into astronomy if I demo my telescope showing the…

crispr is quite easy

Ha! This is HN, I should totally know better than to throw stuff like that out there. I admit, as I wrote the crispr line, in the back of my head I wondered if it was true or not and just went with it because I thought it sounded witty. I stand corrected!

Re: A 13-year-old used my artificial nose to diagnose pneumonia

#182

Post by dekhn »

trulyme wrote: post #155
jboy55 wrote: post #105

Earlier quoted context omitted.

Well one thing is the teen in question probably has little to no exposure to a cohort of humans who have fungal pneumonia to test this on.

This is what I was wondering too. To train a model you need lots of data. How do you get it for such a project?

You would partner with doctors at a research institution that had lots of patients of this type, and the doctors would need to know how to run a clinical trial. But realistically, you would do this in any number of ways using existing samples before running a trial. Tissue samples are fairly easy to get.

Re: A 13-year-old used my artificial nose to diagnose pneumonia

#183

Post by thatcat »

Herodotus38 wrote: post #97
thatcat wrote: post #26

Earlier quoted context omitted.

I doubt that it is possible to differentiate between fungal types using gas sensors trained on spores being released.

I would be interested in what they are testing, it probably wouldn’t be spores but likely something along the lines of biochemical compounds specific to certain species. For example we use blood tests for the presence of https://en.m.wikipedia.org/wiki/Galactomannan to help diagnose invasive aspergillosis.

That requires wetlab work and those compounds usually aren't aerosolized, but i agree it would still be interesting to know the exact details

Re: A 13-year-old used my artificial nose to diagnose pneumonia

#184

Post by causi »

donio wrote: post #123
causi wrote: post #94

Is the headline being a straight-up lie a valid reason for flagging? The kid did not diagnose pneumonia. He came up with an idea for a design that might hypothetically detect pneumonia.

Unfortunately there is no other way to signal trash submissions. "Not upvoting" is not really a sufficient signal when enough people get baited by the headline.

I agree, but I highly suspect that if you flag a lot of submissions that aren't also flagged by others you end up on some kind of list where your flags are ignored or deprioritized.

Re: A 13-year-old used my artificial nose to diagnose pneumonia

#185

Post by 908B64B197 »

lowbloodsugar wrote: post #139
908B64B197 wrote: post #124

Earlier quoted context omitted.

> Is there not more to life than gaming university applications? No. A lot of parents are getting their kids phony medical diagnostics just so they can get extra time on exams. [0] [0] https://www.forbes.com/sites/petergreene/2019/03/16/fake-lea...

But also please be aware that some of them aren't phony.

Most of them aren’t.

And a lot go undiagnosed as well because the parents don’t care/are ashamed/don’t know how to navigate the system.

Re: A 13-year-old used my artificial nose to diagnose pneumonia

#186

Post by westurner »

dekhn wrote: post #173
westurner wrote: post #157

Earlier quoted context omitted.

How much information content is there in DNA (and RNA,)? How do creatures know or learn what not to eat given limited available sensor data?

How much information content is there in DNA? 2 bits per base, before compression. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3220916/ How do creatures know what to eat? Evolution solved that for most creatures, so their sensors don't have to work as hard at runtime. And in other cases, some number of members of a population of creatures will die before the population learns the food is poisonous. Our sensors, and…

So, sensor resolution is higher, there are multiple fields being integrated, in a massively-parallel spreading-activation Biological Neural Network, and that's how blank-slate creatures just know?

Is there enough information content - per the Shannon entropy definition or otherwise - in DNA and/or RNA to code for the survival-selected traits that

I'm not sure that the (Shannon entropy, MIC, Kolmogorov,) information content of the samples is the limit of any given network trained therefrom? Is there anything to be gained from upsampling and adding e.g. gaussian blur (noise)? Maybe it's feature engineering, maybe it's expert methods bias, maybe it's just sensor fusion; that's the magic noise.

Re: A 13-year-old used my artificial nose to diagnose pneumonia

#187

Post by westurner »

westurner wrote: post #186
dekhn wrote: post #173

Earlier quoted context omitted.

How much information content is there in DNA? 2 bits per base, before compression. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3220916/ How do creatures know what to eat? Evolution solved that for most creatures, so their sensors don't have to work as hard at runtime. And in other cases, some number of members of a population of creatures will die before the population learns the food is poisonous. Our sensors, and…

So, sensor resolution is higher, there are multiple fields being integrated, in a massively-parallel spreading-activation Biological Neural Network, and that's how blank-slate creatures just know? Is there enough information content - per the Shannon entropy definition or otherwise - in DNA and/or RNA to code for the survival-selected traits that I'm not sure that the (Shannon entropy, MIC, Kolmogorov,) information c…

Perhaps this is moving the goalposts a bit, but e.g. depixelation does appear to defy such a presumed limit due to apparent information content? Perhaps it is that the network reading the sensor carries additional information associated with the lower-resolution or additional-fields' sensor data?

https://github.com/krantirk/Self-Supervised-photo :

> Given a low-resolution input image, PULSE searches the outputs of a generative model (here, StyleGAN) for high-resolution images that are perceptually realistic and downscale correctly.

Maybe no amount of feature engineering can actually add information?

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