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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

#51

Post by amelius »

hwillis wrote: post #33
amelius wrote: post #25

The main invention is in the electronic nose. The kid just did the plumbing of connecting it to some ML library. Of course, the electronic nose itself is a work of plumbing too, where some existing gas sensors are put on a pcb. In short, nothing seems really new here, but the application is interesting. I guess it's always interesting when people start looking for correlations in data and get some positive results, s…

The sensor (the four gas sensors on the board) was created by a third person. The artificial nose is the TinyML model which trains on the sensor data (CO, NO2, ethanol, VOCs) to detect arbitrary scents by their signatures in those four categories. The fungal pneumonia detector wires up a whole API with azure etc. and trains the model specifically to recognize pneumonia, based on an actual science experiment which gre…

The reason why no engineer has made this yet, is because the medical data was not available to them.

The innovation is in the data, not in the ML.

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

#53

Post by pmarreck »

amelius wrote: post #51
hwillis wrote: post #33

Earlier quoted context omitted.

The sensor (the four gas sensors on the board) was created by a third person. The artificial nose is the TinyML model which trains on the sensor data (CO, NO2, ethanol, VOCs) to detect arbitrary scents by their signatures in those four categories. The fungal pneumonia detector wires up a whole API with azure etc. and trains the model specifically to recognize pneumonia, based on an actual science experiment which gre…

The reason why no engineer has made this yet, is because the medical data was not available to them. The innovation is in the data, not in the ML.

> The innovation is in the data, not in the ML.

can't you kind of say this about all ML? That the main driver in ML is 99% the quality of the training data and 1% the specific details of the neural networks used?

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

#54

Post by ravenstine »

Hmmm... I'm skeptical. Not necessarily because I don't think that pneumonia could be detected by testing VOCs in breath, but because I'm currently working on a project that uses sensors to do breath analysis and my amateur research has informed me that it's fairly hard to get right (which is why my primary goal is to identify deltas rather than achieve numerical accuracy).

For one, VOCs can be present in breath for other reasons besides some sort of infection in the lung, and VOCs are incredibly hard to differentiate with just a sensor. The fact that they tend to be faint in human breath even at their highest (in contrast to O2 and CO2) doesn't help. Even the most expensive PID sensors for VOCs (they get up into the several hundreds a pop) can't really tell you whether the predominant gas is acetone or alcohol or acetaldehyde or hydrogen sulfide. So you've got to figure out whether the presence of VOCs is truly an anomaly and not just a part of ketosis. In which case you will also need to measure at least VeO2 to see whether the VOCs correspond with the Respiratory Quotient.

The "e-nose" project, as described on the MakeZine article, doesn't appear to do that. It does have an alcohol sensor. But these sensors aren't particularly sophisticated. They use semiconductors with heating elements to detect the presence of gases, and there is almost certainly some overlap between the alcohol and VOCs sensors.

If VOCs are produced by pneumonia, then yes, it's conceivable that even just the VOCs sensor alone would detect this. But can this group of sensors used in the e-nose differentiate pneumonia from catabolism?

Maybe? ¯\_(ツ)_/¯

After all, this thing uses AI. And maybe AI can recognize something that a human can't by simply looking at a line graph. I dunno... Such things should be tested against known inputs before being suggested to diagnose anything.

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

#55

Post by Brajeshwar »

mschuster91 wrote: post #40
Brajeshwar wrote: post #23

Cool. And, I have a 13-year and she is still, literally, crying over spilt milk, hacked Roblox merchandize, how done the steak is, why her monitor is tilted wrong, and why I din't warned her before rebooting the primary router.

> and why I din't warned her before rebooting the primary router. Basic sysops rule: either create redundancy (which is hard to do in a consumer space outside of Mac Pro machines as 99.99% of laptops carry only a single LAN port and in towers, about 3/4) or warn your users before doing maintenance.

Well, I do have backups. This is India, so I even have a backup for the backup. I have three ISPs load-balanced, and not experienced any downtime since the beginning of the Pandemic (early 2020). I do realize them going down but we never realize until I looked them up.

It runs almost all the time, but sometimes I need to update settings, etc. which needs reboots the load balancer that distributes everything from.

:-)

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

#56

Post by amelius »

pmarreck wrote: post #53
amelius wrote: post #51

Earlier quoted context omitted.

The reason why no engineer has made this yet, is because the medical data was not available to them. The innovation is in the data, not in the ML.

> The innovation is in the data, not in the ML. can't you kind of say this about all ML? That the main driver in ML is 99% the quality of the training data and 1% the specific details of the neural networks used?

For most real-world applications of ML, yes. Of course, what happens in ML-research is different (where e.g. new networks for new modalities are invented).

But back to the topic, I bet the kid didn't even invent their own neural network topology, but just pulled a predefined network from a library, perhaps without even knowing it. Which is ok, because that is how most people use ML.

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

#57

Post by mrits »

alexk307 wrote: post #2

This is what happens when you give children the tools to succeed by teaching them math and science in ways that directly relate to their world view. Obviously, this kid is very bright, but giving kids the tools to understand how the ideas they're learning can be applied in the real world is so satisfying. They aren't blinded by previous failures, or the current market, or what can and can't be done.

Sometimes you give the children these tools and they decide to do something they are more interested in. It is important to realize that not all children are interested in sciences.

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

#60

Post by tinc293 »

kartben_ wrote: post #34
amelius wrote: post #25

The main invention is in the electronic nose. The kid just did the plumbing of connecting it to some ML library. Of course, the electronic nose itself is a work of plumbing too, where some existing gas sensors are put on a pcb. In short, nothing seems really new here, but the application is interesting. I guess it's always interesting when people start looking for correlations in data and get some positive results, s…

With this reasoning, aren't most things a work of plumbing, and nothing ever really new? And isn't it how innovation happens, at the end of the day?

Well, first of all, you can see those glove holes are too small, that's not the hands of a 13-year-old who mines his own silica. Disgraceful.
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