Tag: ai

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All The Hype About Artificial Intelligence Products Versus What Really Happened!

artificial intelligence products

Flashback to 2018 and 2019, and you can read some of my posts about the RSNA’s latest and greatest artificial intelligence products. So, what percentage of those products has your hospital or imaging center incorporated into their workflow? For us, I can tell you that number is exceedingly low. And, I am willing to bet that most of you have a similar story. So, I figured it would be fun to go through some of the promises that silicon valley has made over the past several years versus what has come to fruition in daily practice. Let’s go over their overpromises and underdelivering. It would be fun to do this every few years to check up on the progression of AI technology in Radiology!

Reading Mammo With Half The Amount of Readers

Ironically, if you have seen any decrease in the number of breast studies coming to your institution, it has far less to do with artificial intelligence. Instead, it is probably related to Covid! Nevertheless, most of the work has returned. And, I don’t know of any institutions that are using artificial intelligence to replace the initial screening reads for mammograms. (as enticing as that sounds!) Most places have the hebeejeebees for ethically, legally, and financially replacing a mammo reader with a computer!

Workflow Will Be Seamlessly Integrated

I was hoping this one would have taken place by now. But to no avail. Yes, we will be getting another EHR/RIS system to replace the one that we have right now. But rumor has it that, although better, it is nowhere near seamless. I am still waiting for the day that I pull up a case, and my computer instantly opens up a case, the appropriate priors, the relevant labs, a brief pertinent history, an internet blurb on the disease entity, and the patient’s most recent surgeries without having to click a button. I believe the day will come. But, I’m not sure it will be there during my working lifetime!

Radiologist Will Have No Role In Reading Bone Ages

This concept makes a lot of sense. AI should read cases with a low likelihood of lawsuits and unlikely dire outcomes. What better study for artificial intelligence to read than a bone age? It certainly meets those criteria. Furthermore, we analyze and match up features of hands with features similar to standard cases. This process should be easy peasy chicken squeezy. (Maybe in my dreams!) Well, I am still waiting for my institution to incorporate this incredible technology!

Dictation Will Be Entirely Automated Into Standard Reports

If I had a dime for every time a company would say, your reports would be so much easier without our technology; I would be a veritable gazillionaire. Of course, they will standardize everything. And, with one button click, the clinician will be able to localize your disease pathology on a film. Where is this technology? Certainly not at our institution. (And, probably not at yours either!)

CAD Artificial Intelligence Products For Mammography Will Work Well Much Better!

Maybe, CAD detection has improved. But, I do not notice it one bit at the institutions I work. For me, it seems like the same old random placement of circles and stars to match supposed masses and calcifications. Rarely (if ever) has it noticeably helped me. And it does not seem to have changed much. Heck, but what do I know?

Artificial Intelligence Products Will Help With Diagnosis On Chest X-Rays

I saw some tremendous potential technologies at the RSNA to help make multiple diagnoses on chest films. It would issue a probability here and there for different disease entities. Well, I have not heard a whisper of this program coming to our institution any time soon. And, I have a sneaking suspicion, you will not see at yours either.

Improved Triage

Finally, I have heard of computer programs that will pre-search for life-altering diagnoses such as intracranial bleeds so that it will draw your attention to these cases first. I would love a program like that, and the technology should not be too advanced. But, I am still waiting and waiting and waiting and waiting…

Still Waiting For These Great Artificial Intelligence Products!

So, where does all of this leave now? I would have to say right back where we started. We have not seen that much yet except for some behind-the-scenes CT and PET-CT image improvement. Let’s do another checkup every once in a while. I have a feeling, though, these products will take a lot longer than anyone initially expected!

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Why Artificial Intelligence (AI) Will Not Take Over Radiology!

AI

Artificial intelligence (AI) is still front and center for the layperson when discussing radiology. Family and friends always ask me why AI will not take over my day job. I had one of those “aha” moments in one of those discussions recently. We discussed how many factors will prevent AI from taking over our jobs anytime soon. These included legal, ethical/moral, and financial reasons. As I was droning on, I realized I could argue why AI could overcome these issues. However, one reason not related to these is why we won’t see a blank screen or a computer person from India, China, or any other country for that matter replacing our presence for a very long time. And that is that medicine is local, not universal. 

Medicine Is Local, Not Universal- AI Cannot Account For It!

“Standards”

Why would differing local “standards” be the most critical reason for keeping radiologists busy? Well, every country and every physician has their opinions about the best way to treat patients. Medicine is not universal. It is local. Yes, a few standards are omnipresent, like the Hippocratic Oath not to harm. But, other standards like lung nodule management vary widely among physicians, counties, states, and countries. The Fleishner criteria for managing pulmonary nodules are not standard. Some folks use that criterion; Others use LI-RADS.; And even others use ELCAP. 

I also know some clinicians that modify all these criteria to fit their patient populations. Therefore, it is only possible to standardize standards in an AI computer algorithm when your physician wants to use a different bar from the rest. One great way to lose the radiology business is to make recommendations that run counter to your referrers!

Management Differences Between Places

Different countries have different standards of care. For example, it would not be appropriate to recommend imaging a patient with an MRI of the shoulder in Canada due to lack of availability. Over there, physicians may be more apt to order a musculoskeletal ultrasound. Likewise, a radiologist in Canada may be more likely to recommend a musculoskeletal ultrasound for a possible rotator cuff tear. Yet, an MRI is part of a routine workup in the United States. Why? Because they have a much more significant backlog of patients waiting to get their studies done with fewer MRIs than we do in the United States.

In China, clinicians may regularly recommend “cupping” for different ailments. How can AI programs account for each cultural difference among countries, states, or counties based on availability, preferences, and cultural norms? These obstacles would be exceedingly difficult to overcome.

Differences Between Surgical And Medical Preferences

We work for other physicians. Our role is to make it easier for them to treat patients. And each clinician has specific needs for caring for their population. Oncologists look at assessment criteria differently from surgeons. Neurosurgeons have different interests than internal medicine doctors when they order a study. An AI program needs to consider all these factors when it summarizes findings and makes recommendations. AI is not ready to make different individualized reports for each subspecialist clinician. It would take massive programming power for which it’s not ready!

Differences Among Individual Patients

And finally, even among patients, culturally speaking, some patients want more aggressive workups, and others are more conservative. For instance, I may have a patient who can’t live with a small complex cyst in their breast and wants it drained. Meanwhile, another patient might be more willing to follow it. Some of these differences may be cultural or related to individual differences. How would an AI program account for that? AI is not ready to interpret every patient’s cultural and emotional status to make these decisions. Again, no supercomputer could make these individual recommendations for patients.

A Radiologists Job Is Still Way Too Complex For AI!

Whether it is differing standards, cultural differences, physician preferences, or individual patient preferences, radiology, in particular, is not a one-size-fits-all discipline. No program can consider all of these issues to replace a radiologist within the foreseeable future. The processing power required to figure this out for every clinician’s report would be enormous. Of course, 500 years later, a program may accomplish all these tasks and replace radiologists. But, by then, the same computer will replace every other job, and no trace of humans may exist as the singularity has come and gone! So, for those thinking about entering radiology, keep these issues from dissuading you. Over your career lifetime, you will still have a job!

 

 

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Does Artificial Intelligence Spell The End For Radiology?

artificial intelligence

Question About Artificial Intelligence:

Greetings, could you elaborate on these words ”(Artificial intelligence) will profoundly affect all of our careers, for better or FOR WORSE” and ”have more to gain and MORE TO LOSE”.

I am asking because, in the above text, you’ve written only about the good things about AI, while with these words, you’re also implying bad things about it, but I, as a reader, don’t know about them as you haven’t listed them.

I am a doctor from Europe whose first specialty choice is radiology, but this artificial intelligence surge is making me think twice about it. Everything I read, including your piece, is a 2-way street ala. ”AI is great, but you must adapt to it.”. The end. Could somebody please tell me HOW I will have to adapt and what the BAD things about AI in the radiology field are? It’s freaking me out! Radiology, as it is now, is a fantastic specialty, but I don’t want to be jobless and incompetent 10,15,20 years from now. It’s a life’s decision, and I have exactly ten days to decide!!

Thanks,

Worried Applicant

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Answer:

You are not alone in worrying about the future of radiology and AI. However, after attending the RSNA meeting and talking to colleagues, AI will not take over a radiologist’s job entirely for a long time (if ever). That aside, AI technology may allow fewer radiologists to do the same amount of work that we do right now. Improving triage, artifacts, and integration will make the radiologist’s job easier.

AI Will Not Take Over The World!

Why do I say this and not worry about AI taking over the world? First, the ability of an algorithm to detect something is only as good as the programmer, the number of data points, and the quality of the data. However, programmers have not optimized the algorithms. The data points are too few. And the quality of the data is not uniform. So, I don’t believe that will happen for many, many years from now.

Moreover, deep learning algorithms still have difficulty distinguishing simple solitary findings on a plain film, such as pneumothorax (often mistaken for chest tubes), let alone all the findings on a chest film. Therefore, I don’t believe the interpreting programs can independently function.

More importantly, companies will not want to accept the consequences of the liability of missing findings on films that go unchecked by a radiologist. So, I see AI as more of a team effort instead of a radical upheaval of all radiologist’s jobs. Let’s spread the liability risk!

What Is The Real Downside Of AI?

With the advent of any new technology, we will see our fair share of crashes, bugs, and technical problems. So, I believe that these would be the main downside. But I think the downside is reasonably limited overall. My advice- if you like radiology, you should go for it. If I were deciding on a profession today, I would not let my fears of AI dissuade me from choosing the radiological field.

My two cents,

Barry Julius, MD