AI: The Doctor That Never Tires?

We asked you for your opinion on the use of Artificial Intelligence (AI) in healthcare, and got the above-depicted, below-described set of results:

• A little over half of respondents to the poll voted for “It speeds up research, and is more methodical about diagnosis, so it’s at least a good extra tool”
• A quarter of respondents voted for “I’m on the fence—it seems to make no more nor less mistakes than human doctors do”
• A little under a fifth of respondents voted for “AI is less prone to fatigue/bias than human doctors, making it an essential new tech”
• Three respondents voted for “AI is a step too far in medical technology, and we’re not ready for it”

Writer’s note: I’m a professional writer (you’d never have guessed, right?) and, apparently, I really did write “no more nor less mistakes”, despite the correct grammar being “no more nor fewer mistakes”. Now, I know this, and in fact, people getting less/fewer wrong is a pet hate of mine. Nevertheless, I erred.

Yet, now that I’m writing this out in my usual software, and not directly into the poll-generation software, my (AI!) grammar/style-checker is highlighting the error for me.

Now, an AI could not do my job. ChatGPT would try, and fail miserably. But can technology help me do mine better? Absolutely!

And still, I dismiss a lot of the AI’s suggestions, because I know my field and can make informed choices. I don’t follow it blindly, and I think that’s key.

AI is less prone to fatigue/bias than human doctors, making it an essential new tech: True or False?

True—with one caveat.

First, a quick anecdote from a subscriber who selected this option in the poll:

❝As long as it receives the same data inputs as my doctor (ie my entire medical history), I can see it providing a much more personalised service than my human doctor who is always forgetting what I have told him. I’m also concerned that my doctor may be depressed – not an ailment that ought to affect AI! I recently asked my newly qualified doctor goddaughter whether she would prefer to be treated by a human or AI doctor. No contest, she said – she’d go with AI. Her argument was that human doctors leap to conclusions, rather than properly weighing all the evidence – meaning AI, as long as it receives the same inputs, will be much more reliable❞

Now, an anecdote is not data, so what does the science say?

Well… It says the same:

❝Of 6695 responding physicians in active practice, 6586 provided information on the areas of interest: 3574 (54.3%) reported symptoms of burnout, 2163 (32.8%) reported excessive fatigue, and 427 (6.5%) reported recent suicidal ideation, with 255 of 6563 (3.9%) reporting a poor or failing patient safety grade in their primary work area and 691 of 6586 (10.5%) reporting a major medical error in the prior 3 months. Physicians reporting errors were more likely to have symptoms of burnout (77.6% vs 51.5%; P<.001), fatigue (46.6% vs 31.2%; P<.001), and recent suicidal ideation (12.7% vs 5.8%; P<.001).❞

See the damning report for yourself: Physician Burnout, Well-being, and Work Unit Safety Grades in Relationship to Reported Medical Errors

AI, of course, does not suffer from burnout, fatigue, or suicidal ideation.

So, what was the caveat?

The caveat is about bias. Humans are biased, and that goes for medical practitioners just the same. AI’s machine learning is based on source data, and the source data comes from humans, who are biased.

See: Bias and Discrimination in AI: A Cross-Disciplinary Perspective

So, AI can perpetuate human biases and doesn’t have a special extra strength in this regard.

The lack of burnout, fatigue, and suicidal ideation, however, make a big difference.

AI speeds up research, and is more methodical about diagnosis: True or False?

True! AI is getting more and more efficient at this, and as has been pointed out, doesn’t make errors due to fatigue, and often comes to accurate conclusions near-instantaneously. To give just one example:

❝Deep learning algorithms achieved better diagnostic performance than a panel of 11 pathologists participating in a simulation exercise designed to mimic routine pathology workflow; algorithm performance was comparable with an expert pathologist interpreting whole-slide images without time constraints. The area under the curve was 0.994 (best algorithm) vs 0.884 (best pathologist).❞

Read: Diagnostic Assessment of Deep Learning Algorithms for Detection of Lymph Node Metastases in Women With Breast Cancer

About that “getting more and more efficient at this”; it’s in the nature of machine learning that every new piece of data improves the neural net being used. So long as it is getting fed new data, which it can process at rate far exceeding humans’ abilities, it will always be constantly improving.

AI makes no more nor less fewer mistakes than humans do: True or False?

False! AI makes fewer, now. This study is from 2021, and it’s only improved since then:

❝Professionals only came to the same conclusions [as each other] approximately 75 per cent of the time. More importantly, machine learning produced fewer decision-making errors than did all the professionals❞

See: AI can make better clinical decisions than humans: study

All that said, we’re not quite at Star Trek levels of “AI can do a human’s job entirely” just yet:

BMJ | Artificial intelligence versus clinicians: pros and cons

To summarize: medical AI is a powerful tool that:

• Makes healthcare more accessible
• Speeds up diagnosis
• Reduces human error

…and yet, for now at least, still requires human oversights, checks and balances.

Essentially: it’s not really about humans vs machines at all. It’s about humans and machines giving each other information, and catching any mistakes made by the other. That way, humans can make more informed decisions, and still keep a “hand on the wheel”.

Antidepressants: Personalization Is Key!

Yesterday, we asked you for your opinions on antidepressants, and got the above-depicted, below-described, set of responses:

• Just over half of respondents said “They clearly help people, but should not be undertaken lightly”
• Just over a fifth of respondents said “They may help some people, but the side effects are alarming”
• Just under a sixth of respondents said “They’re a great way to correct an imbalance of neurochemicals”
• Four respondents said “They are no better than placebo, and are more likely to harm”
• Two respondents said “They merely mask the problem, and thus don’t really help”

So what does the science say?

❝They are no better than placebo, and are more likely to harm? True or False?❞

True or False depending on who you are and what you’re taking. Different antidepressants can work on many different systems with different mechanisms of action. This means if and only if you’re not taking the “right” antidepressant for you, then yes, you will get only placebo benefits:

• Placebo Effect in the Treatment of Depression and Anxiety ← randomly assigned antidepressants are, shockingly, luck of the draw in usefulness
• Antidepressants versus placebo in major depression: an overview ← “wow this science is messy”
• Comparative efficacy and acceptability of 21 antidepressant drugs: a systematic review and network meta-analysis ← “oh look, it makes a difference which antidepressant we give to people”

Rather than dismissing antidepressants as worthless, therefore, it is a good idea to find out (by examination or trial and error) what kind of antidepressant you need, if you indeed do need such.

Otherwise it is like getting a flu shot and being surprised when you still catch a cold!

❝They merely mask the problem, and thus don’t really help: True or False?❞

False, categorically.

The problem in depressed people is the depressed mood. This may be influenced by other factors, and antidepressants indeed won’t help directly with those, but they can enable the person to better tackle them (more on this later).

❝They may help some people, but the side-effects are alarming: True or False?❞

True or False depending on more factors than we can cover here.

Side-effects vary from drug to drug and person to person, of course. As does tolerability and acceptability, since to some extent these things are subjective.

One person’s dealbreaker may be another person’s shrugworthy minor inconvenience at most.

❝They’re a great way to correct an imbalance of neurochemicals: True or False?❞

True! Contingently.

That is to say: they’re a great way to correct an imbalance of neurochemicals if and only if your problem is (at least partly) an imbalance of neurochemicals. If it’s not, then your brain can have all the neurotransmitters it needs, and you will still be depressed, because (for example) the other factors* influencing your depression have not changed.

*common examples include low self-esteem, poor physical health, socioeconomic adversity, and ostensibly bleak prospects for the future.

For those for whom the problem is/was partly a neurochemical imbalance and partly other factors, the greatest help the antidepressants give is getting the brain into sufficient working order to be able to tackle those other factors.

Want to know more about the different kinds?

Here’s a helpful side-by-side comparison of common antidepressants, what type they are, and other considerations:

Mind | Comparing Antidepressants

Want a drug-free approach?

You might like our previous main feature:

The Mental Health First-Aid That You’ll Hopefully Never Need

Take care!