As a radiologist I can say this is an accurate description of the situation. For the time being the AI tools can help perform some simple but tedious tasks, like finding lung nodules or rib fractures, but are no where close to doing the more complex, big picture diagnosis. I look forward to having more of these tools to spend less time on the mundane, and focus more of my attention on those more interesting, cognitively involved tasks which is why I went into radiology in the first place.
Interesting piece! I didn't like this sentence though "Human radiologists spend a minority of their time on diagnostics and the majority on other activities, like talking to patients and fellow clinicians."
The figure for "Interpret images" says 36.4%. Time spent talking to colleagues sums only to 17.8%. The remainders is mainly teaching and interventional radiology. Both of these activities are not something all radiologists do.
So, for the "prototypical" radiologist, the kind that people talk about replacing with AI, I would expect that a majority of time spent on images does seem realistic. Since nobody thinks current AI/robotics can replace nimble-fingered interventional radiologists, it seems a bit misleading to lump interventional radiology with the rest. To a lesser extent, I'd say the same for teaching, certainly not the current focus of AI replacements either.
Also, since I'm being overly anal, I wouldn't count "Meals" and "Personal" in the denominator of a workday either. Guess what, I spend a third of my day asleep, but that doesn't help you understand my job. Surely, the point wasn't that AI can't eat the radiologist's meals yet.
If radiologists are still better at recognizing certain patterns than the models, that suggests that the radiologists have access to more training data than the models. From a policy standpoint, we should be trying to solve this.
As a radiologist I can say this is an accurate description of the situation. For the time being the AI tools can help perform some simple but tedious tasks, like finding lung nodules or rib fractures, but are no where close to doing the more complex, big picture diagnosis. I look forward to having more of these tools to spend less time on the mundane, and focus more of my attention on those more interesting, cognitively involved tasks which is why I went into radiology in the first place.
Interesting piece! I didn't like this sentence though "Human radiologists spend a minority of their time on diagnostics and the majority on other activities, like talking to patients and fellow clinicians."
The figure for "Interpret images" says 36.4%. Time spent talking to colleagues sums only to 17.8%. The remainders is mainly teaching and interventional radiology. Both of these activities are not something all radiologists do.
So, for the "prototypical" radiologist, the kind that people talk about replacing with AI, I would expect that a majority of time spent on images does seem realistic. Since nobody thinks current AI/robotics can replace nimble-fingered interventional radiologists, it seems a bit misleading to lump interventional radiology with the rest. To a lesser extent, I'd say the same for teaching, certainly not the current focus of AI replacements either.
Also, since I'm being overly anal, I wouldn't count "Meals" and "Personal" in the denominator of a workday either. Guess what, I spend a third of my day asleep, but that doesn't help you understand my job. Surely, the point wasn't that AI can't eat the radiologist's meals yet.
I agree. Counting "Meals" and "Personal" in the denominator is highly sus, and borderline offensive.
If radiologists are still better at recognizing certain patterns than the models, that suggests that the radiologists have access to more training data than the models. From a policy standpoint, we should be trying to solve this.
Fantastic piece, and very informative, thank you very much!