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Comment by rscho | Hacker News Reader

You overestimate the data gathering capabilities of the medical system by a huge margin. Even in seemingly objective parameters, you will see: missing data, reporting details dependent on the gatherer, a substantial amount of inaccuracy, etc. etc. Plus, you are describing people who barely know how to use a web browser. And you should also take into account that people driving the system don't even see the value of expert, scientific educated consultancy in those matters. For example, I was just asked to perform "data mining" on a dataset of 150 observations, 400 variables, and ~20% missing data by a renown professor. He told me I was bound to find interesting things in view of his ~400 back-to-back t-tests.

No, I am quite confident in that ML will really take off when data fed to those systems will be automatically gathered.

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Oh god, I missed the passage about the 400 t-tests. Your professor is the guy on the cover of this book:

https://www.statisticsdonewrong.com/

If your comment was a book, I'd lovingly put it on the shelf next to Reinhart's masterpiece ("revised and expanded ... with three times as many statistical errors and examples!"). Unlike Shakespeare, it appears nonfiction is well within the capabilities of the Interwebs (asterisk).

(asterisk) For many years, it was believed that millions of monkeys hitting millions of keyboards would eventually recreate the works of Shakespeare. Now, thanks to the Internet, we know this to be false.

Even in ICUs and NICUs, where it already is being automatically gathered and fed, it turns out that making sensible design and training decisions to get usable performance is harder than anticipated.

News flash, dermatologists don't just look at moles and oncologists don't just do differentials... let's see how these isolated systems deal with cleaning up TKI- and IST-related gastric bleeds, C. diff code browns, and timing chemo around liver resections for sepsis. All in a day at County...

My bet is that clinicians who use AI to amplify their own abilities will come to run the system. Errybody else gets to be a glorified NP, at best, or (worse) administrative ;-)

Ohhh, I thought you were saying that we'll always need doctors to gather the data, but you meant that the ML systems will suck until they get enough data, and they can only get enough data if the process can be automated, so we'll need doctors to do diagnoses until the ML systems stop sucking.

Yes, absolutely.

Doctors can then focus on new diseases, higher level thinking about health, rare cases and such. Under-researched domains can get attention

Yes. People are acting like the medicine problem would be solved if ML could replicate the performance of doctors today.

I hope that, as you said, it will allow doctors to focus on more difficult problems that we did not even think would be possible to tackle.

Not to mention how hard is to have a standardization. Doesn't do any good if the data is not guaranteed to have been measured in somewhat similar conditions. Thinking about my cholesterol. I've seen so much fluctuation on my own blood results between labs. They blame it on the "bad chemical reactives". And that is even a somewhat standardized numerical values, but what about subjective symptom: "I have a sand in eye sensation". For ML this must be translated to a numerical value. Does it feel like a 1 or a 1,5 sensation out of 10, how can we make sure we have the same understanding?

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