Odds radiology will be defunct in ~5-10 years due to automation

[Maxamillion12]

Does anyone have an educated guess on this? Have some interest in this, but not if it goes by the wayside. Thoughts?

---

Members don't see this ad.

 

[ricksimmonsrafowens]

shadow a radiologist and ask what they think!

 

[Maxamillion12]

shadow a radiologist and ask what they think!

I was told this was one of the worst questions you could ask somone

 

[ricksimmonsrafowens]

I was told this was one of the worst questions you could ask somone

that's right! I think you can figure out why.

 

[907914]

that's right! I think you can figure out why.

Because the chances are it is going to go away due to automation/machine learning just like pathology and they are worried about job security?

It is potentially a rude question to ask someone who is in the affected field. If OP is trying to plan a career as a physician and is interested in radiology, wouldn’t lack of job security be one of your concerns before even going down that path?

 

[ricksimmonsrafowens]

Because the chances are it is going to go away due to automation/machine learning just like pathology and they are worried about job security?

if that's what you think, then I suggest not pursuing radiology residency!

 

[907914]

if that's what you think, then I suggest not pursuing radiology residency!

Exactly my point...

 

[meronebib]

You will always want a pair of eyes to confirm anything that is computer generated. That said, I think the main problem for American radiologists is that that task can easily be outsourced to international radiologists at a much cheaper price.

 

[907914]

You will always want a pair of eyes to confirm anything that is computer generated. That said, I think the main problem for American radiologists is that that task can easily be outsourced to international radiologists at a much cheaper price.

I actually worked at a rural hospital where our on call neurologist was an Australian neurologist who just teleconferences in on a Robot he could drive around. The globalization of medicine is crazy and I think awesome.

 

[meronebib]

I actually worked at a rural hospital where our on call neurologist was an Australian neurologist who just teleconferences in on a Robot he could drive around. The globalization of medicine is crazy and I think awesome.

Where’s the human compassion though?!

 

[907914]

Where’s the human compassion though?!

I mean, if you are a patient who needs a neurology consult at 2 am in a 13 bed hospital in a county of 6,000 people, are you more concerned about getting a disease treated or receiving service with a smile?

 

[ricksimmonsrafowens]

I mean, if you are a patient who needs a neurology consult at 2 am in a 13 bed hospital in a county of 6,000 people, are you more concerned about getting a disease treated or receiving service with a smile?

what kind of a neurological scenario in a 13 bed hospital requires a stat consult at 2am? if it's a stroke or a bleed or status the patient should be shipped out to a hospital where they have a neuroICU or interventional neuro or can push tpa

also in your example a physician must have a license in the state they telemedicine to. the doctor may live in australia, but I am 100% sure they are licensed to practice in the US, and as such completed a residency in the US.

 

[907914]

what kind of a neurological scenario in a 13 bed hospital requires a stat consult at 2am? if it's a stroke or a bleed or status the patient should be shipped out to a hospital where they have a neuroICU or interventional neuro or can push tpa

also in your example a physician must have a license in the state they telemedicine to. the doctor may live in australia, but I am 100% sure they are licensed to practice in the US, and as such completed a residency in the US.

I honestly have no clue what the scenario would be. I just know what they had. And you are probably correct, I made no comment on where they performed their residency.

 

[deleted972488]

Even very experienced radiologists (at the top academic medical center where I was treated) missed some IMPORTANT things on my CT scans. As a patient, I would not trust a computer to do this job.

 

[IMGASMD]

I also worked at a hospital with a neurology robot. Thank God our neurologist was 100 miles away that I can transfer to, not 3000 miles away and “I” end up have to do any interventions.

It has been doom and gloom with tele-radiologist coming for years. The night hawk can be anywhere and you don’t even need them in house. I have seen many hospitals with nighthawk, in the end still need someone in-house to verify or sign it in the morning. Due to.... what I am not sure. Maybe regulation, laws, hospital bylaws, protocols? With consolidation of health care systems, hospitals being bought by bigger hospitals, nighthawks haven’t really gained much presence. They have to have someone at the “parent” hospital on-call or a residency program (therefore senior residents) anyway, why send the films outside?

Lastly, a few years ago the big gloom and doom for anesthesia is the automated propofol machine...... you just need a very few cases of any M&M to really stop any machines at this time in history. We chuckle when we see “clinical correlation is recommended”. However, at end of the day, there will be a need for a radiologist (clinician) who can put everything together.

Car can drive itself for years now, it may even do a better job than humans for a while, but we just can’t get it together, not because technology is not there. Liability and responsibility are the name of the game.

I am not a radiologist, so everything just speculation. I am sure if you search hard enough on SDN you’ll find their takes on this.

Edit: clarification.
Also if I remember correctly, there are only some AI applications for radiology right now? Maybe only chest X-ray is good enough.

 

[907914]

Even very experienced radiologists (at the top academic medical center where I was treated) missed some IMPORTANT things on my CT scans. As a patient, I would not trust a computer to do this job.

This is the same logic as "Even a professional bus driver gets in to car crashes. As a transit user, I would not trust a driverless car."

Machine learning only gets better and better. Those top academic radiologists you are talking about are probably at the peak of human performance as far as 'radiology'could be concerned - and they still make mistakes. Machine learning and AI as we know it are barely even scratching the surface of their current potential.

Putting the AI in Radiology - Radiology Today Magazine

Radiology Today newsmagazine reaches 40,000 radiology professionals nationwide on a monthly basis, covering areas such as Radiology Management, Bone Densitometry, Mammography, MRI, PACS, CT, Sonography, Nuclear Medicine, Radiation Oncology, Radiation Therapy, contrast agents, and more!

www.radiologytoday.net

As someone mentioned earlier, you are always (at least as we can currently predict now) going to want a human set of eyes on something to confirm, but even in this 2018 issue of 'Radiology today' it seems there is a great deal of focus on how these technologies can vastly increase workflow, efficiency, and accuracy. With increased workflow there are only two outcomes: either the number of radiologists go down or the clinical scope of radiologists goes up.

 

[ricksimmonsrafowens]

I honestly have no clue what the scenario would be. I just know what they had. And you are probably correct, I made no comment on where they performed their residency.

it's not an issue of where they performed their residency, it's that a lot of lay persons (cough pre-meds) state that medicine can be "sourced out" to other countries, therefore implying it'll be less lucrative to practice in a specialty. it's not really true because to practice telemedicine you have to be licensed in the US, and the physicians practicing telemedicine usually ask for equivalent compensation for their work as a regular attending (maybe higher because of certain liabilities involved).

also, sorry to OP for me being short.... this question of AI in radiology has been rehashed in popular media a lot. Radiology is not going away and a physician will always read the scans in the near future. AI is pretty lame in medicine. Medicine is not that evidence based or really algorithm based. nothing in the near future will replace the clinical gestalt of a physician. that's why pathology slides are not read by AI and will never be, even though it's probably easier to train pattern recognition of an AI on histology slides. the AI isn't even that good at reading EKGs, what's why a physician signs off on them. I wouldn't worry about it.

 

[LongLiveThanos]

If you're worried about radiologists being defunct, then you should also worry about:
Surgeons/Anesthesiologists replaced with robots (da Vinci is collecting data from surgeons).
Internists and PCPs replaced with AI (in testing).

Resulting in no more human doctors except PMNR, which will eventually be replaced with human-like robots.

 

[deleted972488]

I don't think that I would trust a driverless car at this point, either... If AI is proven to be superior to experienced radiologists, fine, but I just don't see that happening any time soon. And there are a lot of people (i.e. patients) still alive who are much more resistant to technology than I.

 

[WedgeDawg]

10 years? 0%

 

[907914]

I don't think that I would trust a driverless car at this point, either... If AI is proven to be superior to experienced radiologists, fine, but I just don't see that happening any time soon. And there are a lot of people (i.e. patients) still alive who are much more resistant to technology than I.

I guess I just approach this topic from the perspective of being a medical laboratory technician seeing automation in the evidence based side of health care first hand.

5 years ago, state of the art chemistry analyzers ran around 20,000 samples per 50 linear feet per day and required 6 technicians, manually checking samples for hemolysis/lipemia/icteremia etc. and a processing department to sort, centrifuge, aliquot and assign to instruments. Today, state of the art runs 75,000 samples per linear 50 feet per 8 hour shift and requires 3 technicians, has a camera to identify any clotting, hemolysis etc. without human intervention, and an entire processing subunit that you literally dump a thousand unspun tubes on to a hopper where it then spins them, produces internal aliquots and sends them to the appropriate instrument. It can even have onboard QC that it draws from on a preset schedule, follow all internal protocols and so on without human intervention. Literally all the technician does is review the ~2-5% of samples that it cannot handle the issue and then review results to make sure they match the patient clinical picture (as far as a bachelors degree person can tell).

Not to compare the difficulties and nuance of radiology to the medical laboratory, but I am just coming from that perspective where automation in the evidence based aide of healthcare is very much real. It is more difficult to automate slide work ups in pathology or sifting through CT scans screening for abnormalities - but if it is a routine task that has regular rules that can be learned/followed then machines can and will eventually do it. If our current state of IS healthcare tells you anything it is that the system doesn’t really care what the patient wants if it makes healthcare delivery more efficient from a profits perspective.

Also, I am just a premed and my premed ego is probably showing. Any physicians that chime in (particularly any radiologists or collaborators on machine learning in medicine) are more likely providing a more accurate answer than I am and these are the personal opinions I hold based on my experiences with healthcare.

 

[Sephirakra]

Does anyone have an educated guess on this? Have some interest in this, but not if it goes by the wayside. Thoughts?

Radiology as a discipline won't be defunct until it's determined who will carry the liability for automated reads. There always has to be someone to sue.

 

[ricksimmonsrafowens]

I guess I just approach this topic from the perspective of being a medical laboratory technician seeing automation in the evidence based side of health care first hand.

5 years ago, state of the art chemistry analyzers ran around 20,000 samples per 50 linear feet per day and required 6 technicians, manually checking samples for hemolysis/lipemia/icteremia etc. and a processing department to sort, centrifuge, aliquot and assign to instruments. Today, state of the art runs 75,000 samples per linear 50 feet per 8 hour shift and requires 3 technicians, has a camera to identify any clotting, hemolysis etc. without human intervention, and an entire processing subunit that you literally dump a thousand unspun tubes on to a hopper where it then spins them, produces internal aliquots and sends them to the appropriate instrument. It can even have onboard QC that it draws from on a preset schedule, follow all internal protocols and so on without human intervention. Literally all the technician does is review the ~2-5% of samples that it cannot handle the issue and then review results to make sure they match the patient clinical picture (as far as a bachelors degree person can tell).

Not to compare the difficulties and nuance of radiology to the medical laboratory, but I am just coming from that perspective where automation in the evidence based aide of healthcare is very much real. It is more difficult to automate slide work ups in pathology or sifting through CT scans screening for abnormalities - but if it is a routine task that has regular rules that can be learned/followed then machines can and will eventually do it. If our current state of IS healthcare tells you anything it is that the system doesn’t really care what the patient wants if it makes healthcare delivery more efficient from a profits perspective.

Also, I am just a premed and my premed ego is probably showing. Any physicians that chime in (particularly any radiologists or collaborators on machine learning in medicine) are more likely providing a more accurate answer than I am and these are the personal opinions I hold based on my experiences with healthcare.

what you're describing is not an AI interpreting whether lab results fit a clinical picture and then the AI suggests a differential diagnosis based on serum and urine lytes and the elements of the HPI... that's something a hospitalist does. What you're describing is just automation of processing samples. not much AI involved.

 

[907914]

what you're describing is not an AI interpreting whether lab results fit a clinical picture and then the AI suggests a differential diagnosis based on serum and urine lytes and the elements of the HPI... that's something a hospitalist does. What you're describing is just automation of processing samples. not much AI involved.

Very true. It is not AI, it is automation of repetitive tasks. Like in that Radiology Today article ^^^ it seems like as it is currently projected for the near future, the automation would simply be increased workflow/efficiency. No diagnosis or recommendations would be made, I assume. But making the workflow more rapid I believe is an inevitability.

 

[getdown]

The chances are the same as the likelihood these ridiculous threads will stop popping up.

 

[ricksimmonsrafowens]

I didn't read the radiology today article. All hospitals and providers want to streamline their workflow and increase productivity... for $$ and providing better quality of care.

 

[Dream of the Endless]

If there is one thing I've learned from cognitive psychology, it's that the majority of people are absolutely terrible at predictions. Even well trained professionals and leading figures in their field are not an exception to this. Example, there was a study done based on the US leading economists and close to none of them predicted anything like the housing crash of 08'. Now every economist, including the ones in the study, think it was inevitable. The human ego is fragile.

My point being, take any prediction into the "distant" future with a grain of salt. Though your question is interesting, and I'm huge into AI and plan to learn a few things about coding among other things after MCAT studying.

What I can tell you for sure is that -right now- the technology already exists to do what you just explained. Look up "IBM's Watson" supercomputer. It's shockingly accurate! And it's no secret that there is significant human error in radiology reads. This holds true even by the -same- radiologist, reading the -same-scan. These two ideas come together to make me think that there is potential for this, but it's impossible to give you an accurate timeline.

What I can also tell you for sure is even IF they did make this technology able to streamlined in the next 10 years, you'd be hard pressed to see it in hospitals immediately. There would need to be clinical trials and regulatory approval to validate that it's safe and effective to use. That would take an unknown amount of time. Even than, you'll still need a few radiologist to verify their reads during it's early rollout. I'd say you're safe for the next 10 years. 20-50 years? That's impossible to predict.

Also, don't let these people make you feel stupid for asking these questions. It's a valid concern, even if the timeline isn't. The operators of horse carriage didn't picture themselves getting replaced by the car. Now in hindsight, it seemed inevitable.

Edit: If you're truly interested in this topic, and those like it, as it directly relates to medicine there is a new book called "Deep Medicine, how AI can make healthcare human again" by some cardiologist named Eric Tropol. Directly touches on this topic apparently as well. I heard about it at the end of last year, and it is now available. I also plan on reading it after MCAT lol

 

[Maxamillion12]

If there is one thing I've learned from cognitive psychology, it's that the majority of people are absolutely terrible at predictions. Even well trained professionals and leading figures in their field are not an exception to this. Example, there was a study done based on the US leading economists and close to none of them predicted anything like the housing crash of 08'. Now every economist, including the ones in the study, think it was inevitable. The human ego is fragile.

My point being, take any prediction into the "distant" future with a grain of salt. Though your question is interesting, and I'm huge into AI and plan to learn a few things about coding among other things after MCAT studying.

What I can tell you for sure is that -right now- the technology already exists to do what you just explained. Look up "IBM's Watson" supercomputer. It's shockingly accurate! And it's no secret that there is significant human error in radiology reads. This holds true even by the -same- radiologist, reading the -same-scan. These two ideas come together to make me think that there is potential for this, but it's impossible to give you an accurate timeline.

What I can also tell you for sure is even IF they did make this technology able to streamlined in the next 10 years, you'd be hard pressed to see it in hospitals immediately. There would need to be clinical trials and regulatory approval to validate that it's safe and effective to use. That would take an unknown amount of time. Even than, you'll still need a few radiologist to verify their reads during it's early rollout. I'd say you're safe for the next 10 years. 20-50 years? That's impossible to predict.

Also, don't let these people make you feel stupid for asking these questions. It's a valid concern, even if the timeline isn't. The operators of horse carriage didn't picture themselves getting replaced by the car. Now in hindsight, it seemed inevitable.

Edit: If you're truly interested in this topic, and those like it, as it directly relates to medicine there is a new book called "Deep Medicine, how AI can make healthcare human again" by some cardiologist named Eric Tropol. Directly touches on this topic apparently as well. I heard about it at the end of last year, and it is now available. I also plan on reading it after MCAT lol

What specialty is most safe from automation?

 

[Maxamillion12]

The chances are the same as the likelihood these ridiculous threads will stop popping up.

Why do you think this?

 

[efle]

It's not going to go away entirely as a field but the numbers needed will probably be reduced. For example you could probably safely automate a lot of routine stuff and leave only the gray areas or complex cases to the fully trained radiologists.

I mean look to anesthesia and the rise of CRNAs. Anesthesiology isn't gone, but the numbers needed to staff certain floors has gone way down now that you can just have one gas doc supervising a dozen CRNA rooms each doing routine GI scoping procedures.

Pathology same idea, you aren't going to fully replace the docs but surely a huge part of the routine biopsy reads can be shifted to machines, or less trained persons assisted by machines.

I personally wouldn't worry about 5-10 years from now, but our careers are going to be more like 30+ years. I'll be absolutely shocked if rads and path resemble their current selves in the year 2050.

 

[Maxamillion12]

It's not going to go away entirely as a field but the numbers needed will probably be reduced. For example you could probably safely automate a lot of routine stuff and leave only the gray areas or complex cases to the fully trained radiologists.

I mean look to anesthesia and the rise of CRNAs. Anesthesiology isn't gone, but the numbers needed to staff certain floors has gone way down now that you can just have one gas doc supervising a dozen CRNA rooms each doing routine GI scoping procedures.

Pathology same idea, you aren't going to fully replace the docs but surely a huge part of the routine biopsy reads can be shifted to machines, or less trained persons assisted by machines.

I personally wouldn't worry about 5-10 years from now, but our careers are going to be more like 30+ years. I'll be absolutely shocked if rads and path resemble their current selves in the year 2050.

Going to be more like what?

 

[AnatomyGrey12]

also, sorry to OP for me being short.... this question of AI in radiology has been rehashed in popular media a lot. Radiology is not going away and a physician will always read the scans in the near future. AI is pretty lame in medicine. Medicine is not that evidence based or really algorithm based. nothing in the near future will replace the clinical gestalt of a physician. that's why pathology slides are not read by AI and will never be, even though it's probably easier to train pattern recognition of an AI on histology slides. the AI isn't even that good at reading EKGs, what's why a physician signs off on them. I wouldn't worry about it.

This. AI can't even read basic EKGs, and I can tell you that a basic chest film is a lot more difficult than a basic EKG. Rads isn't going anywhere anytime soon.

Also, I am just a premed and my premed ego is probably showing.

Yes.

 

[Maxamillion12]

This. AI can't even read basic EKGs, and I can tell you that a basic chest film is a lot more difficult than a basic EKG. Rads isn't going anywhere anytime soon.


Yes.

But aren't the preclinical years all memorization too? Couldn't all doctors be replaced? One thing that strikes me is that despite all of this innovation, we still haven't replaced things like fast food workers, cashiers to the full degree

 

[ricksimmonsrafowens]

But aren't the preclinical years all memorization too? Couldn't all doctors be replaced?

lol. I suggest that you shadow a physician and see how clinical decisions are made in real time.

 

[Maxamillion12]

Suggest that you shadow a physician and see how clinical decision is made in real time.

I have. Can't medicine be broken down into you have X pain -> So it has to be Y location. And X is not associated with W or Z, so this has to be the differential diagnosis

 

[ricksimmonsrafowens]

I have. Can't medicine be broken down into you have X pain -> So it has to be Y location. And X is not associated with W or Z, so this has to be the differential diagnosis

80% of patients cant even give me a reliable history to do what you describe lol. That's why it takes a really long time to become an attending, because you're learning how to exercise appropriate clinical judgement based on limited or potentially false information. I suggest you shadow in the ED, ICU, critical care and see how decisions are made in real time.

 

[Maxamillion12]

80% of patients cant even give me a reliable history to do what you describe lol. That's why it takes a really long time to become an attending, because you're learning how to exercise appropriate clinical judgement based on limited or potentially false information. I suggest you shadow in the ED, ICU, critical care and see how decisions are made in real time.

I have. A machine could easily sift through vitals and figuring out electrolyte abnormalities and piece things together based on probability

 

[Dream of the Endless]

What specialty is most safe from automation?

Major key: The safest spot is to become part robot. Solves all your problems. High human interaction. "I don't want to speak with your automated machine. Give me an operator."

But aren't the preclinical years all memorization too? Couldn't all doctors be replaced? One thing that strikes me is that despite all of this innovation, we still haven't replaced things like fast food workers, cashiers to the full degree

Machine cashiers are a thing at many McDonald's. Automated food lines are also a thing at many grocery lines. Just because the option is there, doesn't mean it is what everyone wants. The consumer is always right, or so they say.

I have. Can't medicine be broken down into you have X pain -> So it has to be Y location. And X is not associated with W or Z, so this has to be the differential diagnosis

Your questions and thought process seems to be all over the place. I feel that you would benefit from some targeted reading and shadowing. Perhaps go work as a scribe?

 

[ricksimmonsrafowens]

I have. A machine could easily sift through vitals and figuring out electrolyte abnormalities and piece things together based on probability

shifting thru lytes (lol) and vitals is not what practicing medicine is lol

 

[AnatomyGrey12]

But aren't the preclinical years all memorization too? Couldn't all doctors be replaced? One thing that strikes me is that despite all of this innovation, we still haven't replaced things like fast food workers, cashiers to the full degree

Lol no. Pre-clinical years are akin to someone in training to be a pilot and learning the names of all the buttons and their basic function.

I have. Can't medicine be broken down into you have X pain -> So it has to be Y location. And X is not associated with W or Z, so this has to be the differential diagnosis

No. I mean sure I guess if every patient came in the form of a UWorld question but they don't.

I have. A machine could easily sift through vitals and figuring out electrolyte abnormalities and piece things together based on probability

This quote shows you literally have no idea what medicine is.

 

[IMGASMD]

I have. Can't medicine be broken down into you have X pain -> So it has to be Y location. And X is not associated with W or Z, so this has to be the differential diagnosis

I will take that with a grain of salt. If that’s what you truly believe, why don’t you just go write a program and automate medicine? You made it sound so simple, logical and straightforward.

If you want to make money, medicine isn’t where it’s at. If you want job security, pick something that you don’t think can be replaced. If you want fame, clinical practice isn’t where it’s at.

As the other poster had said, go shadow someone or a speciality a decision has to be made under distress or conflicting goals have to be weighed.

Even in primary care: “AI” decided metoprolol is the drug best for HTN, tachycardia, and occasional arrhythmia after you (the young hot clinical AI designer) input all the symptoms.
“Doc, my insurance wouldn’t pay for it....”
But it’s the best medication, because my algorithm told me.
“Doc, but they would pay for some other drug, la-something-lol..”
Would you then just prescribe it? Labetalol. Without remembering that the patient is a asthmatic who is on two daily inhalers?

I know this is probably over your head, but it takes most people at least 4 years of medical school and 3 years of residency to get to an adequate level to do this. I tell people, we call medicine a “practice” for a reason.

Pick something YOU want to do for your own reasons.

 

[getdown]

I have. Can't medicine be broken down into you have X pain -> So it has to be Y location. And X is not associated with W or Z, so this has to be the differential diagnosis

I have. A machine could easily sift through vitals and figuring out electrolyte abnormalities and piece things together based on probability

Please stop. You have no ****ing clue what you're talking about. It's extremely insulting to all practicing physicians that you would even say this. The amount of thought process that goes into making a decision of what's going on is not simply X Y Z and definitely beyond the comprehension of some premed who did 20? hours of shadowing. So please. Stop talking about things you have absolutely zero understanding about. And no I will not explain anything further because for you to even understand me, you would have to at least had basic physiology and pathophysiology under your belt.

 

[Maxamillion12]

Please stop. You have no ****ing clue what you're talking about. It's extremely insulting to all practicing physicians that you would even say this. The amount of thought process that goes into making a decision of what's going on is not simply X Y Z and definitely beyond the comprehension of some premed who did 20? hours of shadowing. So please. Stop talking about things you have absolutely zero understanding about. And no I will not explain anything further because for you to even understand me, you would have to at least had basic physiology and pathophysiology under your belt.

Didn't mean it like this. All I'm saying is that 10 mins ago, everyone was saying that Rads could be replaced, now people are offended by the idea that other specialties can be replaced. The same type of thinking could extend to primary care specialties.

 

[907914]

Didn't mean it like this. All I'm saying is that 10 mins ago, everyone was saying that Rads could be replaced, now people are offended by the idea that other specialties can be replaced. The same type of thinking could extend to primary care specialties.

Rads/Path type where “If the Cell looks like this, it is *insert cancer score like the Gleason score for prostate*” or “This shaded area is an inclusion like XXXX and layered images can be produced” are fairly algorithms based. However, even those types of things that will likely be automated to a major degree will merely be automation of the identification process and will inherently be programmed to produce a lot of false positives (so that it catches the largest spread and nothing is missed). And they will not be offering a full differential diagnosis (at least not for the foreseeable future), they will be increasing workflow.

 

[Maxamillion12]

Rads/Path type where “If the Cell looks like this, it is *insert cancer score like the Gleason score for prostate*” or “This shaded area is an inclusion like XXXX and layered images can be produced” are fairly algorithms based. However, even those types of things that will likely be automated to a major degree will merely be automation of the identification process and will inherently be programmed to produce a lot of false positives (so that it catches the largest spread and nothing is missed). And they will not be offering a full differential diagnosis (at least not for the foreseeable future), they will be increasing workflow.

Now this makes more sense. Don't know why that guy got so hurt

 

[getdown]

Now this makes more sense. Don't know why that guy got so hurt

Why? Because you've never went through the pain of residency. The 24 hour calls, sleepless nights doing trauma, juggling multiple issues at the same time, dealing with life and death choices. And someone then implies that you can simply subsitute that all with a computer algorithm is simply insulting. Even if you didn't mean to come across like that your comments trivialized the actual medical decision and training that all physicians go through. Even if it was simply looking at slides of cells, context and patient history matter in deciding what's more likely.

Let this be a learning opportunity for you to really think before asking as to how your questions come off the other person. This will serve you well if you ever make it into the hospital or you're going to be in for a rude awakening.

 

[mega_]

I think there is a chance that radiology actually will become more important. Now hear me out. As AI assisted interpretation will become more accurate, the guidelines when to do an imaging study will expand significantly. At the end of the day, someone will need to review and sign interpretations. I think similarly in pathology, precision-based medicine will significantly expand the arsenal of tools that pathologists can have at their disposal, such as growing microtumors and testing drugs on them, sequencing complex genes and gene expression profiles, expanding antibody arsenal for immunochemistry, etc. Overall you will need more people to run things. At the same time, hopefully, we will get more accurate in our assessment and treatment.

 

[Maxamillion12]

What do people think of this article here?

With an estimated 160,000 deaths in 2018, lung cancer is the most common cause of cancer death in the United States1. Lung cancer screening using low-dose computed tomography has been shown to reduce mortality by 20–43% and is now included in US screening guidelines1,2,3,4,5,6. Existing challenges include inter-grader variability and high false-positive and false-negative rates7,8,9,10. We propose a deep learning algorithm that uses a patient’s current and prior computed tomography volumes to predict the risk of lung cancer. Our model achieves a state-of-the-art performance (94.4% area under the curve) on 6,716 National Lung Cancer Screening Trial cases, and performs similarly on an independent clinical validation set of 1,139 cases. We conducted two reader studies. When prior computed tomography imaging was not available, our model outperformed all six radiologists with absolute reductions of 11% in false positives and 5% in false negatives. Where prior computed tomography imaging was available, the model performance was on-par with the same radiologists. This creates an opportunity to optimize the screening process via computer assistance and automation. While the vast majority of patients remain unscreened, we show the potential for deep learning models to increase the accuracy, consistency and adoption of lung cancer screening worldwide.

End-to-end lung cancer screening with three-dimensional deep learning on low-dose chest computed tomography - Nature Medicine

A convolutional neural network performs automated prediction of malignancy risk of pulmonary nodules in chest CT scan volumes and improves accuracy of lung cancer screening.

www.nature.com

 

[VincentAdultman]

You premeds should just stop persuing med school and design robo docs. Sounds like you all have this sht figured out.

 

[Maxamillion12]

You premeds should just stop persuing med school and design robo docs. Sounds like you all have this sht figured out.

Most of the docs only attack here without giving an explanation.