Everything else besides the above in TFA is extraneous. Machine learning models could have absolute perfect performance at zero cost, and the above would make it so that radiologists are not going to be "replaced" by ML models anytime soon.
Everything else besides the above in TFA is extraneous. Machine learning models could have absolute perfect performance at zero cost, and the above would make it so that radiologists are not going to be "replaced" by ML models anytime soon.
>Human radiologists spend a minority of their time on diagnostics and the majority on other activities, like talking to patients and fellow clinicians.
The vast majority of radiologists do nothing other than: come in (or increasingly, stay at home), sit down at a computer, consume a series of medical images while dictating their findings, and then go home.
If there existed some oracle AI that can always accurately diagnose findings from medical images, this job literally doesn't need to exist. It's the equivalent of a person staring at CCTV footage to keep count of how many people are in a room.
I think it may be selection bias.
Generalizing this to all radiologists is just as wrong as the original article saying that radiologists don't spend the majority of their time reading images. Yes, some diagnostic radiologists can purely read and interpret images and file their results electronically (often remotely through PACS systems). But the vast majority of radiology clinics where I live have a radiologist on-site, and as one example, results for suspicious mammograms where I live in Texas are always given by a radiologist.
And as the other comment said, many radiologists who spend the majority of their time reading images also perform a number of procedures (e.g. stereotactic biopsies).
I could have just gone to med school and never deal with layoffs, RTO, etc.
I also recently had surgery and the surgeon talked to the radiologist to discuss my MRI before operating.
It's sort of like saying "sometimes a cab driver talks to passengers and suggests a nice restaurant nearby, so you can't automate it away with a self-driving cab."
She also said that she frequently talks to the them before ordering scans to consult on what imaging she’s going to order.
> It's sort of like saying "sometimes a cab driver talks to passengers and suggests a nice restaurant nearby, so you can't automate it away with a self-driving cab."
It’s more like if 3/100 kids who took a robot taxi died, suffered injury, had to undergo unnecessary invasive testing, or were unnecessarily admitted to the hospital.
Does that sounds like an assistance's job?
In the same fashion as construction worker just shows up, "performs a series of construction tasks", then go home. We just need to make a machine that performs "construction tasks" and we can build cities, railways and road networks for nothing but the cost of the materials!
Perhaps this minor degree of oversimplification is why the demise of radiologists have been so frequently predicted?
Do you have some kind of source? This seems unlikely.
The current "workflow" is primary care physician (or specialist) -> radiology tech that actually does the measurement thing -> radiologist for interpretation/diagnosis -> primary care physician (or specialist) for treatment.
If you have perfect diagnosis, it could be primary care physician (or specialist) -> radiology tech -> ML model for interpretation -> primary care physician (or specialist.
PCPs don't have the training and aren't paid enough for that exposure.
To understand why, you would really need to take a good read of the average PCP's malpractice policy.
The policy for a specialist would be even more strict.
You would need to change insurance policies before your workflow was even possible from a liability perspective.
Basically, the insurer wants, "a throat to choke", so to speak. Handing up a model to them isn't going to cut it anymore than handing up Hitachi's awesome new whiz-bang proton therapy machine would. They want their pound of flesh.
Human radiologists have them. They can miss things: false negative. They can misdiagnose things: false positive.
Interviews have them. A person can do well, be hired and turn out to be bad employee: false positive. A person who would have been a good employee can do badly due to situational factors and not get hired: false negative.
The justice system has them. An innocent person can be judged guilty: false positive. A guilty person can be judged innocent: false negative.
All policy decisions are about balancing out the false negatives against the false positives.
Medical practice is generally obsessed with stamping out false negatives: sucks to be you if you're the doctor who straight up missed something. False positives are avoided as much as possible by defensive wording that avoids outright affirming things. You never say the patient has the disease, you merely suggest that this finding could mean that the patient has the disease.
Hiring is expensive and firing even more so depending on jurisdiction, so corporations want to minimize false positives as much as humanly possible. If they ever hire anyone, they want to be sure it's absolutely the right person for them. They don't really care that they might miss out on good people.
There are all sorts of political groups trying to tip the balance of justice in favor of false negatives or false positivies. Some would rather see guilty go free than watch a single innocent be punished by mistake. Others don't care about innocents at all. I could cite some but it'd no doubt lead to controversy.
If you're getting a blood test, the pipeline might be primary care physician -> lab with a nurse to draw blood and machines to measure blood stuff -> primary care physician to interpret the test results. There is no blood-test-ologist (hematologist?) step, unlike radiology.
Anyway, "there's going to be radiologists around for insurance reasons only but they don't bring anything else to patient care" is a very different proposition from "there's going to be radiologists around for insurance reasons _and_ because the job is mostly talking to patients and fellow clinicians".
And it would be the developer's throat that gets choked when something goes awry.
I'm betting developers will want to take on neither the cost of insurance, nor the increased risk of liability.
HackerNews is often too quick to reply with a “well actually” that they miss the overall point.
How often do they talk to patients? Every time I have ever had an x-ray, I have never talked to a radiologist. Fellow clinicians? Train the xray tech up a bit more.
If the mote is 'talking to people' that is a mote that doesn't need an MD, or at least not a full specialization MD. ML could kill radiologist MD, radiologist could become the job title of a nurse or x-ray tech specialized in talking to people about the output.
That's fine. But then the xray tech becomes the radiologist, and that becomes the point in the workflow that the insurer digs out the malpractice premiums.
In essence, your xray techs would become remarkably expensive. Someone is talking to the clinicians about the results. That person, whatever you call them, is going to be paying the premiums.
Is this uncommon in the rest of the US?