9 ms·

The sample size is 22 patients. Also, I've noticed the definition of the word "AI" has grown to encompass pretty much any type of software that does something

The sample size is 22 patients. Also, I've noticed the definition of the word "AI" has grown to encompass pretty much any type of software that does something with data.

leoh 7y ago
I think it's ok to call this AI, but I agree that it's a little misleading. I think a better way to describe much of AI these days is pattern recognition. Incredible pattern recognition, to be clear, but pattern recognition. Agreed about the sample size. It's not clear from the article whether the high accuracy was based on testing against the training set, too. I assume not, as that would be exceptionally sloppy. But it's not clear.
denhaus 7y ago
Good catch, I don’t think they mention that in the main article (at least in reader view). In this case I guess the “AI” label is relatively well applied (compared to the scope of ALL things I’ve seen it haphazardly slapped on), but yeah, still - people need to stop calling any kind of data analysis “AI”.
etbebl 7y ago
What, do you think that's too low? Sounds pretty normal for this type of study. Of course, that does mean the results don't necessarily generalize to the whole population, which is why you do eventually need much larger sample sizes when you're working toward FDA approval.
- brenden2 7y ago
  It seems a little premature to proclaim "Near-Perfect Accuracy" on such a small sample size. It sounds to me like they may have overfit their model.
- ska 7y ago
  > don't necessarily generalize to the whole population In my experience it is far more likely to mean "doesn't generalize well, and moving to a reasonable training set will reveal flaws in the model.
Scea91 7y ago
Also accuracy is not a good measure for evaluating detection of rare events such as seizures. (https://arxiv.org/pdf/1812.01388.pdf https://arxiv.org/pdf/1812.01388.pdf)
freeflight 7y ago
> Also, I've noticed the definition of the word "AI" has grown to encompass pretty much any type of software that does something with data. Afaik AGI research is still a separate thing, so it's not really that misleading to use "AI" for applications like this were machine learning is involved, resulting in a very specialized "artificial intelligence" that can spot otherwise hidden patterns.
hodgesrm 7y ago
> Also, I've noticed the definition of the word "AI" has grown to encompass pretty much any type of software that does something with data. That's definitely the case in conferences like O'Reilly Strata. They seem to be 100% focused on AI/ML, which seems really limiting. I'm starting to skip attendance until things get a bit more balanced.

The sample size is 22 patients. Also, I've noticed the definition of the word "AI" has grown to encompass pretty much any type of software that does something with data.

leoh 7y ago

I think it's ok to call this AI, but I agree that it's a little misleading. I think a better way to describe much of AI these days is pattern recognition. Incredible pattern recognition, to be clear, but pattern recognition. Agreed about the sample size. It's not clear from the article whether the high accuracy was based on testing against the training set, too. I assume not, as that would be exceptionally sloppy. But it's not clear.

denhaus 7y ago

Good catch, I don’t think they mention that in the main article (at least in reader view). In this case I guess the “AI” label is relatively well applied (compared to the scope of ALL things I’ve seen it haphazardly slapped on), but yeah, still - people need to stop calling any kind of data analysis “AI”.

etbebl 7y ago

What, do you think that's too low? Sounds pretty normal for this type of study. Of course, that does mean the results don't necessarily generalize to the whole population, which is why you do eventually need much larger sample sizes when you're working toward FDA approval.

brenden2 7y ago
It seems a little premature to proclaim "Near-Perfect Accuracy" on such a small sample size. It sounds to me like they may have overfit their model.
ska 7y ago
> don't necessarily generalize to the whole population In my experience it is far more likely to mean "doesn't generalize well, and moving to a reasonable training set will reveal flaws in the model.

Scea91 7y ago

Also accuracy is not a good measure for evaluating detection of rare events such as seizures. (https://arxiv.org/pdf/1812.01388.pdf https://arxiv.org/pdf/1812.01388.pdf)

freeflight 7y ago

> Also, I've noticed the definition of the word "AI" has grown to encompass pretty much any type of software that does something with data. Afaik AGI research is still a separate thing, so it's not really that misleading to use "AI" for applications like this were machine learning is involved, resulting in a very specialized "artificial intelligence" that can spot otherwise hidden patterns.

hodgesrm 7y ago

> Also, I've noticed the definition of the word "AI" has grown to encompass pretty much any type of software that does something with data. That's definitely the case in conferences like O'Reilly Strata. They seem to be 100% focused on AI/ML, which seems really limiting. I'm starting to skip attendance until things get a bit more balanced.