5 ms·

I'm entering radiology residency, and I'm very pro-automation / machine learning. There's a contentious debate in the field about whether radiologists will be r

I'm entering radiology residency, and I'm very pro-automation / machine learning. There's a contentious debate in the field about whether radiologists will be replaced: https://forums.studentdoctor.net/threads/will-ai-replace-radiologists.1210227/ https://forums.studentdoctor.net/threads/will-ai-replace-rad... HackerNews is very developer-focused. If you guys saw what a radiologist does on a 9-5 basis you'd be amazed it hasn't already been automated. Sitting behind a computer, looking at images and writing a note takes up 90% of a radiologist's time. There are innumerable tools to help radiologists read more images in less time: Dictation software, pre-filled templates, IDE-like editors with hotkeys for navigating reports, etc. There are even programs that automate the order in which images are presented so a radiologist can read high-complexity cases early, and burn through low-complexity ones later on. What's even more striking is that the field of radiology is standardized, in stark contrast to the EMR world. All images are stored on PACS which communicate using DICOM and HL7. The challenges to full-automation are gaining access to data, training effective models, and, most importantly, driving user adoption. If case volumes continue to rise, radiologists will be more than happy to automate additional steps of their workflow. Edit: A lot of push back from radiologist is in regards to the feasibility of automated reads, as these have been preached for years with few coming to fruition. I like to point out that the deep learning renaissance in computer vision started in 2012 with AlexNet; this stuff is very new, more effective, and quite different than previous models.

patothon 10y ago
Have you heard about http://www.heartflow.com/ http://www.heartflow.com/ ?
- aabajian 10y ago
  Yes! Stanford has started (at least) two radiology imaging companies. Heartflow and iSchemView (formerly RAPID): http://www.ischemaview.com/ http://www.ischemaview.com/ These are examples of next-generation radiology companies. The current generation of products are focused on image storage and display. These new companies offer automated image analysis before the radiologist even looks at the image. iSchemaView does hemorrhage maps as soon as new head CT or head MRI is acquired.
sarthakjain 10y ago
Have any of the methods made radiologists more efficient? If you were to imagine a system that made a radiologist 10x more efficient what would it look like?
- aabajian 10y ago
  Yes, massive increases in efficiency. A radiologist can read anywhere from 50-100 images per day (depending on modality CXR/MR/CT/etc). Voice dictation is ubiquitous and residents are trained from the beginning on how to navigate the templating software. There are three areas that take a lot of time that radiologist would like to see automated: 1. Counting lung nodules. 2. Working mammography CAD. 3. Automated bone-age determination. Those are the hot three topics for machine learning. Personally, I think that a normal vs. non-normal classifier for CXRs would be more interesting because you could have a completely generated note for normal reads, and radiologists could just quickly look at the image without writing/dictating anything. Of note, hospitals and radiology departments typically lose money on X-ray reads because the reimbursement is $7-$20 (compared to $100+ for MR/CT). So if you could halve the read time, they might become profitable again. Edit: In terms of 10x, what you'd want is a system that would automatically make the reads (i.e. radiologist report), and a very efficient way for radiologist to verify what is written. It's hard to make a pathologic read, but since roughly 50% of reads are normal, you could start with normal reports.
- kakoni 10y ago
  Before even going to AI/ML type of things, our startup (www.radfox.fi) is doing "simple" fixes to current workflows, first making sure radiology referrals are at the same time informative and decisive (=quality and accuracy of the referral) And then bringing checklist driven analysis for radiologist.
deleted 10y ago
[deleted]
epmatsw 10y ago
When I looked at HL7 a few years back, it was standardized on in the most technical sense and was basically a big bag of hurt. Epic made a big chunk of their money just charging people to build interfaces over various PACS (and other) systems. Has that changed recently?
- aabajian 10y ago
  Yes and no. I spoke with an Epic engineer recently and he confirmed that Epic is still a front-end to HL7 databases. With that said, many PACS are adopting the WADO standard (https://www.research.ibm.com/haifa/projects/software/wado/ https://www.research.ibm.com/haifa/projects/software/wado/), which provides a REST interface to radiology images. It makes it a lot easier to retrieve images for analysis, albeit you'd still have to implement DICOM/HL7 if you want to make a usable product.
- kayman 10y ago
  HL7 has matured even more now. The linear evolution from HL7 v2 to HL7 v3 did not win the day. Most are now moving to https://www.hl7.org/fhir/ https://www.hl7.org/fhir/ Main issue is with HL7 is not technical. From a business point of view, the incentive to cooperate with other systems via HL7 means another reason for a department to adopt a system other than yours.
- sufyanadam 10y ago
  Ruby makes working with things like HL7 super easy. Check out the super extensible HL7 ruby parser I wrote here: https://github.com/sufyanadam/simple_hl7_parser https://github.com/sufyanadam/simple_hl7_parser. It currently focuses on parsing ORU messages but can be easily extended to support any HL7 segment. Feel free to submit a PR :)
amelius 10y ago
> The challenges to full-automation are gaining access to data, [...] It looks like everybody sitting on their data is hindering progress. Is there anything that can be done about that politically? I mean, in many cases the data belongs to the public anyway, unless people signed a waiver, but what is the legality of that?
cridenour 10y ago
As someone who just struggled through writing a DICOM parser, _standardized_ doesn't always mean the same. For more examples, see RETS in the real estate world :)
- dorianm 10y ago
  For those curious: - Some RETS recorded requests/responses: https://github.com/estately/rets/blob/master/test/vcr_cassettes/unauthorized_response.yml https://github.com/estately/rets/blob/master/test/vcr_casset... (Basically some XML-based (SOAP?), cookie + authorization, that seems very ASP.net / Windows Server centric) - DICOM ("It includes a file format definition and a network communications protocol"): https://en.wikipedia.org/wiki/DICOM https://en.wikipedia.org/wiki/DICOM It's basically how to imaging devices communicate and store the images. Image examples: http://www.osirix-viewer.com/resources/dicom-image-library/ http://www.osirix-viewer.com/resources/dicom-image-library/ A video of what a doctor would see: https://www.youtube.com/watch?v=Prb5lcR8Jqw https://www.youtube.com/watch?v=Prb5lcR8Jqw TCP-based protocol in Wireshark: https://wiki.wireshark.org/Protocols/dicom https://wiki.wireshark.org/Protocols/dicom I wrote a little .dcm to .jpg based on ruby-dicom BTW: https://gist.github.com/Dorian/9e3eb5891b49926c15a05c641ffefb3b https://gist.github.com/Dorian/9e3eb5891b49926c15a05c641ffef... - PACS seems just like a database model basically http://mehmetsen80.github.io/EasyPACS/ http://mehmetsen80.github.io/EasyPACS/ It's the server that is gonna give the info to the doctors. It's interesting how there seems to be only one popular viewer: OsiriX
  - dimlyaware 10y ago
    Thank you! This helped hugely
hackpert 10y ago
I'm curious, how hard do you think it is to integrate new tech with the systems currently being used in radiology? Are the file formats and standards largely proprietary/closed?
- aabajian 10y ago
  It's not too difficult to make your own PACS, there's even open-source software for this. However, you need to be compliant and this usually means obtaining FDA approval of any device you want to install on the hospital network.
chadcmulligan 10y ago
PACS developer here - I asked the same thing a few years ago when I started in pACS about automation. I was told it's the need to have someone to sue that holds back the automation, not so much the technology.
- taneq 10y ago
  Wouldn't that objection disappear once automation is more reliable than a human operator, since the human operator would be less likely to be sued when taking responsibility for an automated system's results than they would for simply trying to make the call themselves?
  - jackyinger 10y ago
    It's more about who gets sued. If you make software to fully automate interpretation you would be the party sued. If there is still a human in the loop, you are not liable for their errors.
    - taneq 10y ago
      I don't understand how that works - if you're an employee of a company, generally the company is liable for mistakes you make (unless you're also a director of the company). So for the company, whether they choose to provide their services based on the output of some software or based on the judgement of a human employee, the result should be the same. I can see an argument that if the company was sued then it could try to push the blame onto the software vendor, but surely that would be decided based on the contract between company and software vendor, which is usually defined by the software license.
      - foota 10y ago
        The person operating the machinery is not working for the company that makes it though.
    - asher_ 10y ago
      This seems absurd. Are there any examples you can point to, or legal principle you are referencing here?
neves 10y ago
20 years ago I did some software to analyze satellite images of the Amazon to monitor deforestation. We got a result that matched the quality of human experts. The problem has always been political and economical, not technological.
- aabajian 10y ago
  I agree, nevertheless it's exciting to see some progress being made (see the heart flow and iSchemaView companies cited below). Incidentally, there is a new angle to the radiologists push back - interventional radiologist are generally quite in favor of automating reads. This year IR is its own specialty, but coupled to three years of DR training. This is the speciality that I'm entering. I want to be an interventionalist while advocating for the adoption of machine learning systems on the diagnostic side.
- spuz 10y ago
  I'm not sure if there was more to your story that you missed. Was your software successful? Is it in use today? Is automation widespread in the study of Amazonian deforestation?
  - tomsmeding 10y ago
    Software not being used all over the place does not mean the software is bad, generally.
  - neves 10y ago
    No. No. No. :-)
- i336_ 10y ago
  How did your software work, what techniques was it using, and what was the surrounding context relating to the data that was fed in and the output the model gave? There might be some interesting things that can be learned from this kind of info and applied to the current status quo (I'm definitely not arguing that there is a sociopolitical element).
metaobject 10y ago
About 5 years ago while observing an echcardiogram I remarked to the radiologist that this was something that could be automated eventually. I don't think she took too kindly to my remark. She was measuring the distance between various structures etc. and I recall thinking about how to implement something to reproduce what she as doing.
jsferrei 10y ago
I was talking to a friend in medicine about this recently. Is total automation actually required right now? As others have said, I'm sure politics is a big chunk of why that hasn't happened yet. What if we had tools to help radiologists identify where they should focus their attention in a particular image, and even give them some hinting specific to the contents of that particular image. It would not only save time, but have the added benefit of helping stave off errors caused by fatigue.
computerex 10y ago
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3372692/ https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3372692/ Machine learning is already used in Radiology. Chances are eventually Radiology will be the domain of machines. But it's going to take some time to get there. Healthcare is extremely regulated and closed minded. Most of the people in the thread you listed above are clearly biased towards medicine and against computer science and machine learning. But machine learning has been having success in diagnostic medicine even well before the deep learning boom that thread talks about. For example: http://ieeexplore.ieee.org/abstract/document/1617200/ http://ieeexplore.ieee.org/abstract/document/1617200/
- code777777 10y ago
  Agreed, in theory it's possible to create a tricorder-like system. Basically, radiology and advanced diagnostics in a box.
elihu 10y ago
I suppose full automation may be a long way off, but maybe in the mean time we can do both? Have the radiologist evaluate the images, and then look at the report the AI generated and see if they agree. Use the radiologist to help train the AI, and use the AI to double-check the radiologist. Maybe if MRI scans get cheap enough (due to advances in cheap superconductors or whatever) that it's economically feasible to scan people regularly as a precautionary measure (rather than in response to some symptom), then the bulk of the cost might then be in having the radiologist look at the scans. In those "there's nothing wrong but lets check anyways" cases, it might be better to just have the AI do it all even if its accuracy is lower, if it represents a better health-care-dollar-spent to probability-of-detecting-a-serious-problem ratio. (If the alternative is to just not do the scan because the radiologist's fees are too expensive, then it's better to have the cheap scan than nothing at all.)
sufyanadam 10y ago
I wrote a really simple ruby gem to parse HL7 into ruby. It's super easy to extend, all you have to do is define a new class containing a function-to-column map. The key is the name of the function to call against a HL7 segment and the value is the position of the element in HL7 segment that you want the function to return. Check it out here: https://github.com/sufyanadam/simple_hl7_parser https://github.com/sufyanadam/simple_hl7_parser
PatentTroll 10y ago
Can confirm. Have a friend who is in radiology residency, and I was completely shocked when I found out what radiologists do. When I told him that his job will be automated before he retires, he argued profusely against automation. But it's primarily an image recognition task, which computers are quite good at already and will likely improve.
ohstopitu 10y ago
my mom (an anesthesiologist) wanted me to become a doctor and do my masters in radiology. So I decided to observe an radiologist at an hospital for a day (back in 2011), and I noticed that most if not all of it was already automated. Radiologists were there to rubber-stamp the machine's work (and to ensure compliance, laws and what not).
sdflkj 10y ago
Wow. It is crazy how uninformed you all are (no offense). Radiologists do not just look at an image and say "white thing there!". They incorporate the appearance, characteristics, anatomy, pathophysiology, patient's clinical history/age/medications/surgical history, and combine all of that information into some image findings but more importantly a focused differential diagnosis for the clinician. We have had computers reading EKGs for decades (a 2D line) and they still get it wrong 50+ percent of the time. No machine is taking over EKG's any time soon. I'm sure machines will someday take over radiology but there will be many, many jobs automated before it (i.e. decades).
sdflkj 10y ago
Wow. It is crazy how uninformed you all are (no offense). Radiologists do not just look at an image and say "white thing there!". They incorporate the appearance, characteristics, anatomy, pathophysiology, patient's clinical history/age/medications/surgical history, and combine all of that information into some image findings but more importantly a focused differential diagnosis for the clinician. We have had computers reading EKGs for decades (a 2D line) and they still get it wrong 50+ percent of the time. No machine is taking over EKG's any time soon. I'm sure machines will someday take over radiology but there will be many, many jobs automated before it (i.e. decades).

patothon 10y ago

Have you heard about http://www.heartflow.com/ http://www.heartflow.com/ ?

aabajian 10y ago
Yes! Stanford has started (at least) two radiology imaging companies. Heartflow and iSchemView (formerly RAPID): http://www.ischemaview.com/ http://www.ischemaview.com/ These are examples of next-generation radiology companies. The current generation of products are focused on image storage and display. These new companies offer automated image analysis before the radiologist even looks at the image. iSchemaView does hemorrhage maps as soon as new head CT or head MRI is acquired.

sarthakjain 10y ago

Have any of the methods made radiologists more efficient? If you were to imagine a system that made a radiologist 10x more efficient what would it look like?

aabajian 10y ago
Yes, massive increases in efficiency. A radiologist can read anywhere from 50-100 images per day (depending on modality CXR/MR/CT/etc). Voice dictation is ubiquitous and residents are trained from the beginning on how to navigate the templating software. There are three areas that take a lot of time that radiologist would like to see automated: 1. Counting lung nodules. 2. Working mammography CAD. 3. Automated bone-age determination. Those are the hot three topics for machine learning. Personally, I think that a normal vs. non-normal classifier for CXRs would be more interesting because you could have a completely generated note for normal reads, and radiologists could just quickly look at the image without writing/dictating anything. Of note, hospitals and radiology departments typically lose money on X-ray reads because the reimbursement is $7-$20 (compared to $100+ for MR/CT). So if you could halve the read time, they might become profitable again. Edit: In terms of 10x, what you'd want is a system that would automatically make the reads (i.e. radiologist report), and a very efficient way for radiologist to verify what is written. It's hard to make a pathologic read, but since roughly 50% of reads are normal, you could start with normal reports.
kakoni 10y ago
Before even going to AI/ML type of things, our startup (www.radfox.fi) is doing "simple" fixes to current workflows, first making sure radiology referrals are at the same time informative and decisive (=quality and accuracy of the referral) And then bringing checklist driven analysis for radiologist.

deleted 10y ago

[deleted]

epmatsw 10y ago

When I looked at HL7 a few years back, it was standardized on in the most technical sense and was basically a big bag of hurt. Epic made a big chunk of their money just charging people to build interfaces over various PACS (and other) systems. Has that changed recently?

aabajian 10y ago
Yes and no. I spoke with an Epic engineer recently and he confirmed that Epic is still a front-end to HL7 databases. With that said, many PACS are adopting the WADO standard (https://www.research.ibm.com/haifa/projects/software/wado/ https://www.research.ibm.com/haifa/projects/software/wado/), which provides a REST interface to radiology images. It makes it a lot easier to retrieve images for analysis, albeit you'd still have to implement DICOM/HL7 if you want to make a usable product.
kayman 10y ago
HL7 has matured even more now. The linear evolution from HL7 v2 to HL7 v3 did not win the day. Most are now moving to https://www.hl7.org/fhir/ https://www.hl7.org/fhir/ Main issue is with HL7 is not technical. From a business point of view, the incentive to cooperate with other systems via HL7 means another reason for a department to adopt a system other than yours.
sufyanadam 10y ago
Ruby makes working with things like HL7 super easy. Check out the super extensible HL7 ruby parser I wrote here: https://github.com/sufyanadam/simple_hl7_parser https://github.com/sufyanadam/simple_hl7_parser. It currently focuses on parsing ORU messages but can be easily extended to support any HL7 segment. Feel free to submit a PR :)

amelius 10y ago

> The challenges to full-automation are gaining access to data, [...] It looks like everybody sitting on their data is hindering progress. Is there anything that can be done about that politically? I mean, in many cases the data belongs to the public anyway, unless people signed a waiver, but what is the legality of that?

cridenour 10y ago

As someone who just struggled through writing a DICOM parser, _standardized_ doesn't always mean the same. For more examples, see RETS in the real estate world :)

dorianm 10y ago
For those curious: - Some RETS recorded requests/responses: https://github.com/estately/rets/blob/master/test/vcr_cassettes/unauthorized_response.yml https://github.com/estately/rets/blob/master/test/vcr_casset... (Basically some XML-based (SOAP?), cookie + authorization, that seems very ASP.net / Windows Server centric) - DICOM ("It includes a file format definition and a network communications protocol"): https://en.wikipedia.org/wiki/DICOM https://en.wikipedia.org/wiki/DICOM It's basically how to imaging devices communicate and store the images. Image examples: http://www.osirix-viewer.com/resources/dicom-image-library/ http://www.osirix-viewer.com/resources/dicom-image-library/ A video of what a doctor would see: https://www.youtube.com/watch?v=Prb5lcR8Jqw https://www.youtube.com/watch?v=Prb5lcR8Jqw TCP-based protocol in Wireshark: https://wiki.wireshark.org/Protocols/dicom https://wiki.wireshark.org/Protocols/dicom I wrote a little .dcm to .jpg based on ruby-dicom BTW: https://gist.github.com/Dorian/9e3eb5891b49926c15a05c641ffefb3b https://gist.github.com/Dorian/9e3eb5891b49926c15a05c641ffef... - PACS seems just like a database model basically http://mehmetsen80.github.io/EasyPACS/ http://mehmetsen80.github.io/EasyPACS/ It's the server that is gonna give the info to the doctors. It's interesting how there seems to be only one popular viewer: OsiriX
- dimlyaware 10y ago
  Thank you! This helped hugely

hackpert 10y ago

I'm curious, how hard do you think it is to integrate new tech with the systems currently being used in radiology? Are the file formats and standards largely proprietary/closed?

aabajian 10y ago
It's not too difficult to make your own PACS, there's even open-source software for this. However, you need to be compliant and this usually means obtaining FDA approval of any device you want to install on the hospital network.

chadcmulligan 10y ago

PACS developer here - I asked the same thing a few years ago when I started in pACS about automation. I was told it's the need to have someone to sue that holds back the automation, not so much the technology.

taneq 10y ago
Wouldn't that objection disappear once automation is more reliable than a human operator, since the human operator would be less likely to be sued when taking responsibility for an automated system's results than they would for simply trying to make the call themselves?
- jackyinger 10y ago
  It's more about who gets sued. If you make software to fully automate interpretation you would be the party sued. If there is still a human in the loop, you are not liable for their errors.
  - taneq 10y ago
    I don't understand how that works - if you're an employee of a company, generally the company is liable for mistakes you make (unless you're also a director of the company). So for the company, whether they choose to provide their services based on the output of some software or based on the judgement of a human employee, the result should be the same. I can see an argument that if the company was sued then it could try to push the blame onto the software vendor, but surely that would be decided based on the contract between company and software vendor, which is usually defined by the software license.
    - foota 10y ago
      The person operating the machinery is not working for the company that makes it though.
  - asher_ 10y ago
    This seems absurd. Are there any examples you can point to, or legal principle you are referencing here?

neves 10y ago

20 years ago I did some software to analyze satellite images of the Amazon to monitor deforestation. We got a result that matched the quality of human experts. The problem has always been political and economical, not technological.

aabajian 10y ago
I agree, nevertheless it's exciting to see some progress being made (see the heart flow and iSchemaView companies cited below). Incidentally, there is a new angle to the radiologists push back - interventional radiologist are generally quite in favor of automating reads. This year IR is its own specialty, but coupled to three years of DR training. This is the speciality that I'm entering. I want to be an interventionalist while advocating for the adoption of machine learning systems on the diagnostic side.
spuz 10y ago
I'm not sure if there was more to your story that you missed. Was your software successful? Is it in use today? Is automation widespread in the study of Amazonian deforestation?
- tomsmeding 10y ago
  Software not being used all over the place does not mean the software is bad, generally.
- neves 10y ago
  No. No. No. :-)
i336_ 10y ago
How did your software work, what techniques was it using, and what was the surrounding context relating to the data that was fed in and the output the model gave? There might be some interesting things that can be learned from this kind of info and applied to the current status quo (I'm definitely not arguing that there is a sociopolitical element).

metaobject 10y ago

About 5 years ago while observing an echcardiogram I remarked to the radiologist that this was something that could be automated eventually. I don't think she took too kindly to my remark. She was measuring the distance between various structures etc. and I recall thinking about how to implement something to reproduce what she as doing.

jsferrei 10y ago

I was talking to a friend in medicine about this recently. Is total automation actually required right now? As others have said, I'm sure politics is a big chunk of why that hasn't happened yet. What if we had tools to help radiologists identify where they should focus their attention in a particular image, and even give them some hinting specific to the contents of that particular image. It would not only save time, but have the added benefit of helping stave off errors caused by fatigue.

computerex 10y ago

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3372692/ https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3372692/ Machine learning is already used in Radiology. Chances are eventually Radiology will be the domain of machines. But it's going to take some time to get there. Healthcare is extremely regulated and closed minded. Most of the people in the thread you listed above are clearly biased towards medicine and against computer science and machine learning. But machine learning has been having success in diagnostic medicine even well before the deep learning boom that thread talks about. For example: http://ieeexplore.ieee.org/abstract/document/1617200/ http://ieeexplore.ieee.org/abstract/document/1617200/

code777777 10y ago
Agreed, in theory it's possible to create a tricorder-like system. Basically, radiology and advanced diagnostics in a box.

elihu 10y ago

I suppose full automation may be a long way off, but maybe in the mean time we can do both? Have the radiologist evaluate the images, and then look at the report the AI generated and see if they agree. Use the radiologist to help train the AI, and use the AI to double-check the radiologist. Maybe if MRI scans get cheap enough (due to advances in cheap superconductors or whatever) that it's economically feasible to scan people regularly as a precautionary measure (rather than in response to some symptom), then the bulk of the cost might then be in having the radiologist look at the scans. In those "there's nothing wrong but lets check anyways" cases, it might be better to just have the AI do it all even if its accuracy is lower, if it represents a better health-care-dollar-spent to probability-of-detecting-a-serious-problem ratio. (If the alternative is to just not do the scan because the radiologist's fees are too expensive, then it's better to have the cheap scan than nothing at all.)

sufyanadam 10y ago

I wrote a really simple ruby gem to parse HL7 into ruby. It's super easy to extend, all you have to do is define a new class containing a function-to-column map. The key is the name of the function to call against a HL7 segment and the value is the position of the element in HL7 segment that you want the function to return. Check it out here: https://github.com/sufyanadam/simple_hl7_parser https://github.com/sufyanadam/simple_hl7_parser

PatentTroll 10y ago

Can confirm. Have a friend who is in radiology residency, and I was completely shocked when I found out what radiologists do. When I told him that his job will be automated before he retires, he argued profusely against automation. But it's primarily an image recognition task, which computers are quite good at already and will likely improve.

ohstopitu 10y ago

my mom (an anesthesiologist) wanted me to become a doctor and do my masters in radiology. So I decided to observe an radiologist at an hospital for a day (back in 2011), and I noticed that most if not all of it was already automated. Radiologists were there to rubber-stamp the machine's work (and to ensure compliance, laws and what not).

sdflkj 10y ago

Wow. It is crazy how uninformed you all are (no offense). Radiologists do not just look at an image and say "white thing there!". They incorporate the appearance, characteristics, anatomy, pathophysiology, patient's clinical history/age/medications/surgical history, and combine all of that information into some image findings but more importantly a focused differential diagnosis for the clinician. We have had computers reading EKGs for decades (a 2D line) and they still get it wrong 50+ percent of the time. No machine is taking over EKG's any time soon. I'm sure machines will someday take over radiology but there will be many, many jobs automated before it (i.e. decades).

sdflkj 10y ago