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The New Coffee Room

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  2. General Discussion
  3. Radiologists vs AI

Radiologists vs AI

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  • JonJ Offline
    JonJ Offline
    Jon
    wrote on last edited by
    #1

    The good news is after they’re pwned by the computer a few times they can probably learn to take discrepancies a bit more seriously.

    Doctor PhibesD 1 Reply Last reply
    • JonJ Jon

      The good news is after they’re pwned by the computer a few times they can probably learn to take discrepancies a bit more seriously.

      Doctor PhibesD Offline
      Doctor PhibesD Offline
      Doctor Phibes
      wrote on last edited by
      #2

      @Jon said in Radiologists vs AI:

      The good news is after they’re pwned by the computer a few times they can probably learn to take discrepancies a bit more seriously.

      I'd guess that the next generation of pretty much everybody is going to be a lot more adept at working with AI

      I was only joking

      Aqua LetiferA 1 Reply Last reply
      • George KG Offline
        George KG Offline
        George K
        wrote on last edited by
        #3

        I've seen reports of stuff like this in the past - before the term "AI" became popular. I suppose it's inevitable that machine learning can spot things that the human eye can't see or ignore.

        This may be one of the reasons that Interventional Radiology appears to be getting more popular - it's literally "hands on" as opposed to "eyes on."

        "Now look here, you Baltic gas passer... " - Mik, 6/14/08

        The saying, "Lite is just one damn thing after another," is a gross understatement. The damn things overlap.

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        • KlausK Offline
          KlausK Offline
          Klaus
          wrote on last edited by
          #4

          @George-K I would imagine that a major benefit of AI-based CT scan diagnosis would be that one could feed it way more images than a human radiologist could ever handle. Like, say, a CT with ten images per millimeter, from toe to hair. Maybe for something like all-purpose cancer screening.

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          • AxtremusA Offline
            AxtremusA Offline
            Axtremus
            wrote on last edited by
            #5

            One barrier to human-AI collaboration is the inability of AI to “explain” its inferences. Given an input, an AI model can tell you this input maps to that output, but it cannot explain to you “why” it mapped the input to that particular output. “Explainable AI” is still a big, unresolved problem.

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            • KlausK Offline
              KlausK Offline
              Klaus
              wrote on last edited by
              #6

              I would say "explainable machine learning" is a big unresolved problem. Or, even more specifically, "explainable deep neural networks".

              Other forms of AI are perfectly explainable. For instance, SAT solvers usually generate a concrete counterexample if they reject a formula.

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              • Doctor PhibesD Doctor Phibes

                @Jon said in Radiologists vs AI:

                The good news is after they’re pwned by the computer a few times they can probably learn to take discrepancies a bit more seriously.

                I'd guess that the next generation of pretty much everybody is going to be a lot more adept at working with AI

                Aqua LetiferA Offline
                Aqua LetiferA Offline
                Aqua Letifer
                wrote on last edited by
                #7

                @Doctor-Phibes said in Radiologists vs AI:

                @Jon said in Radiologists vs AI:

                The good news is after they’re pwned by the computer a few times they can probably learn to take discrepancies a bit more seriously.

                I'd guess that the next generation of pretty much everybody is going to be a lot more adept at working with AI

                I called the radiology shit about 8 months ago. Just sayin'.

                Please love yourself.

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