4 ms·

I worked on a similar pipeline for renal cell carcinoma a few years ago [1], although we only published a small subset of results since parts of the pipeline (e

I worked on a similar pipeline for renal cell carcinoma a few years ago [1], although we only published a small subset of results since parts of the pipeline (e.g., finding representative tiles, survival prediction) had better results being produced elsewhere in the lab. Regarding the hook in the headline -- computers surpassing pathologists -- it's a bit like automated driving in that even if true the immediate problem is the social and economic system. That is, we're not going to be removing the pathologist from the diagnostic and prognostic process anytime soon for many reasons, so how instead do we leverage machine learning in concert with the human observer to improve the diagnostic system? For that reason, decision introspection may be as valuable a topic of research as improving classification accuracy: justifying a particular automated classification to the pathologist, directing them to representative regions, and describing regions of feature space in biological terms. [1] http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=6945104 http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=6945104

mgreg 10y ago
Very good point. Even if this particular study isn't a "breakthrough" it is likely a matter of time before AI / Deep Learning (what term am I supposed to use?) is able to better interpret visual data than a human. The real barriers to adoption of such a technology are significant and can be witnessed in the popular Self Driving Car technology race. Many people seem to believe the technology problem has already been solved or will be shortly but regulations, public perception, and adjacent industries (i.e. insurance) must adapt before we actually see self driving cars for the common man. These tend to be slow moving beasts. Given how many applications we're seeing for AI it seems that there may be a battle for attention of lawmakers and others for which AI application we put into production first given the limited bandwidth our regulators have; it's not like congress has been especially productive over the last many years.
_0ffh 10y ago
This! As far as I can remember, the experience in chess is that a human+computer team beats either of them working alone (sorry, can't find a reference just now).
- daveguy 10y ago
  I would love to believe this is true, unfortunately I do not think it is. Computer chess algorithms completely blow away human competitors. The strongest human, Magnus Carlsen has an elo rating of 2857 [0]. Stockfish, the strongest chess algorithm (open source, btw) has an elo rating of 3445 [1]. Computer chess algorithms are so much stronger than humans that if the human second guesses the algorithm -- the human is probably wrong. You may have been thinking of this bbc article [2] in which an amateur cyborg player beat grandmaster cyborg players -- the amateurs were crunching additional metadata about what situations were best for their play. However, they didn't beat stockfish, they beat other cyborg players. [0] https://ratings.fide.com/card.phtml?event=1503014 https://ratings.fide.com/card.phtml?event=1503014 [1] http://www.computerchess.org.uk/ccrl/404/ http://www.computerchess.org.uk/ccrl/404/ [2] http://www.bbc.com/future/story/20151201-the-cyborg-chess-players-that-cant-be-beaten http://www.bbc.com/future/story/20151201-the-cyborg-chess-pl...
  - billforsternz 10y ago
    The top humans and top computers never play each other anymore, and so the rating pools are independent and not comparable. I suppose Stockfish would grind Magnus down in a serious match, but only because the human player is susceptible to fatigue. The teams that tune the engines for engine v engine matches would never dream of letting them make up their own moves in the opening phase, instead they use human openings, an acknowledgement that humans understand the game better.
    - pbhjpbhj 10y ago
      >an acknowledgement that humans understand the game better. // How is that true? I'd imagine it's to reduce the search space against human players and to make use of records of games played - a large corpus of which have involved traditional openings. It doesn't seem to imply the acknowledgement claimed?
      - billforsternz 10y ago
        Sorry I "replied" in a sibling node since no reply link was present at the time (maybe reply links only appear after a timeout?)
deleted 10y ago
[deleted]
praccu 10y ago
Agreed. I published a paper on exactly that ( augmenting scientists searching for novel materials, rather than replacing scientists entirely). One of the benefits is that you can often model simpler problems which are more tractable. http://www.nature.com/nature/journal/v533/n7601/full/nature17439.html http://www.nature.com/nature/journal/v533/n7601/full/nature1...

mgreg 10y ago

Very good point. Even if this particular study isn't a "breakthrough" it is likely a matter of time before AI / Deep Learning (what term am I supposed to use?) is able to better interpret visual data than a human. The real barriers to adoption of such a technology are significant and can be witnessed in the popular Self Driving Car technology race. Many people seem to believe the technology problem has already been solved or will be shortly but regulations, public perception, and adjacent industries (i.e. insurance) must adapt before we actually see self driving cars for the common man. These tend to be slow moving beasts. Given how many applications we're seeing for AI it seems that there may be a battle for attention of lawmakers and others for which AI application we put into production first given the limited bandwidth our regulators have; it's not like congress has been especially productive over the last many years.

_0ffh 10y ago

This! As far as I can remember, the experience in chess is that a human+computer team beats either of them working alone (sorry, can't find a reference just now).

daveguy 10y ago
I would love to believe this is true, unfortunately I do not think it is. Computer chess algorithms completely blow away human competitors. The strongest human, Magnus Carlsen has an elo rating of 2857 [0]. Stockfish, the strongest chess algorithm (open source, btw) has an elo rating of 3445 [1]. Computer chess algorithms are so much stronger than humans that if the human second guesses the algorithm -- the human is probably wrong. You may have been thinking of this bbc article [2] in which an amateur cyborg player beat grandmaster cyborg players -- the amateurs were crunching additional metadata about what situations were best for their play. However, they didn't beat stockfish, they beat other cyborg players. [0] https://ratings.fide.com/card.phtml?event=1503014 https://ratings.fide.com/card.phtml?event=1503014 [1] http://www.computerchess.org.uk/ccrl/404/ http://www.computerchess.org.uk/ccrl/404/ [2] http://www.bbc.com/future/story/20151201-the-cyborg-chess-players-that-cant-be-beaten http://www.bbc.com/future/story/20151201-the-cyborg-chess-pl...
- billforsternz 10y ago
  The top humans and top computers never play each other anymore, and so the rating pools are independent and not comparable. I suppose Stockfish would grind Magnus down in a serious match, but only because the human player is susceptible to fatigue. The teams that tune the engines for engine v engine matches would never dream of letting them make up their own moves in the opening phase, instead they use human openings, an acknowledgement that humans understand the game better.
  - pbhjpbhj 10y ago
    >an acknowledgement that humans understand the game better. // How is that true? I'd imagine it's to reduce the search space against human players and to make use of records of games played - a large corpus of which have involved traditional openings. It doesn't seem to imply the acknowledgement claimed?
    - billforsternz 10y ago
      Sorry I "replied" in a sibling node since no reply link was present at the time (maybe reply links only appear after a timeout?)

deleted 10y ago

[deleted]

praccu 10y ago

Agreed. I published a paper on exactly that ( augmenting scientists searching for novel materials, rather than replacing scientists entirely). One of the benefits is that you can often model simpler problems which are more tractable. http://www.nature.com/nature/journal/v533/n7601/full/nature17439.html http://www.nature.com/nature/journal/v533/n7601/full/nature1...