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SYSK Selects: Will Computers Replace Doctors? · Stuff You Should Know

• 0:01
  Speaker 1: Hey, everybody, it's me Josh and for this week's s
• 0:03
  Speaker 1: Y s K Selex, I've chosen will computers replaced doctors.
• 0:08
  Speaker 1: It's an episode so dated I still wore a fitbit
• 0:11
  Speaker 1: when we recorded it. No, but seriously, it is a
• 0:15
  Speaker 1: really interesting episode. And even though we recorded it years ago,
• 0:19
  Speaker 1: the stuff that we're talking about still quite hasn't come
• 0:22
  Speaker 1: to fruition. So sit back and enjoy this peek into
• 0:26
  Speaker 1: the future. Welcome to Stuff you should know, a production
• 0:33
  Speaker 1: of My Heart Radios How Stuff Works. Hey, and welcome
• 0:41
  Speaker 1: to the podcast. I'm Josh Clark. There's Charles W. Chuck Bryant,
• 0:44
  Speaker 1: our guest producer Noel is here. Yeah, Jerry needs a
• 0:48
  Speaker 1: buffer day from her Christmas break. I can't say that again. No,
• 0:53
  Speaker 1: she's at home on her buffer day. And the freezing
• 0:56
  Speaker 1: cold because we record these somewhat in advance, we are
• 1:00
  Speaker 1: in the midst of the polar vortex and um, yeah,
• 1:04
  Speaker 1: everyone's just talking about how cold it is. We're back.
• 1:06
  Speaker 1: It is our first recording after the holidays. It's literally
• 1:09
  Speaker 1: freezing cold up. So welcome back, buddy. Thanks, Welcome back
• 1:12
  Speaker 1: to you too. Even though this will be what like
• 1:13
  Speaker 1: late January, it will be a balmy sixteen. I think
• 1:17
  Speaker 1: the end of the end of January. When is when
• 1:19
  Speaker 1: this one comes out? All right, Well, happy New Year
• 1:21
  Speaker 1: and happy New Year to YouTube, and happy holidays to you.
• 1:24
  Speaker 1: Thanks um Chuck, Yes, sir, you're feeling good. You're loose,
• 1:28
  Speaker 1: You're ready. I'm loose. So you see this, you've seen
• 1:31
  Speaker 1: this before. Yeah, your Fitbit, My fit bit is that
• 1:33
  Speaker 1: buzz marketing. Not really, It's just a really good example. Um.
• 1:38
  Speaker 1: I feel like fit Bit. I'm not like necessarily loyal
• 1:42
  Speaker 1: to it or anything like that. They don't pay me
• 1:44
  Speaker 1: money to mention the podcast. Sometimes I'll just be like,
• 1:48
  Speaker 1: stop staring at me. Fit Bit. Yeah, um, but no,
• 1:50
  Speaker 1: I like it. I'm happy with it. Um I I
• 1:53
  Speaker 1: pointed out though, because it's part of this to me,
• 1:58
  Speaker 1: and I don't think it's over confirmation bias. It seems
• 2:00
  Speaker 1: like there really is a growing desire among just average
• 2:05
  Speaker 1: ordinary people to be able to track there their health,
• 2:11
  Speaker 1: their well being, their activity. Um, and to do it easily. Yeah,
• 2:16
  Speaker 1: we have tools now that make it like that thing
• 2:19
  Speaker 1: super convenient. Yeah, it's in fit It's not the only one.
• 2:21
  Speaker 1: There's like Nike fuel Band. There's Jawbone is another really
• 2:24
  Speaker 1: good one. There's others like um that track uh, your
• 2:28
  Speaker 1: galvanic response, so they're able to put that together with
• 2:32
  Speaker 1: respiration and heartbeat and come up with a pretty good
• 2:35
  Speaker 1: assessment of how many calories you're burning at any given time,
• 2:38
  Speaker 1: which is like kind of a holy grail with this
• 2:40
  Speaker 1: kind of thing right now. Um, there's others that track
• 2:43
  Speaker 1: your sleep. There's apps out there that let you, um
• 2:47
  Speaker 1: track your mood. Um. There's sites like quantified self, which
• 2:51
  Speaker 1: are basically like people trying to push wearable technology like
• 2:55
  Speaker 1: this further into the future. There's entire websites like share
• 3:00
  Speaker 1: care dot com that are dedicated to health information and
• 3:03
  Speaker 1: health um uh support yeah, self advocacy, yeah. And and
• 3:08
  Speaker 1: there's this It seems to me, this desire to kind
• 3:11
  Speaker 1: of say, hey, this is my health, this is my body.
• 3:14
  Speaker 1: I want to know more about it, you know, totally
• 3:17
  Speaker 1: Like I don't want to necessarily cut out doctors, but
• 3:21
  Speaker 1: I I want to decide if I should go to
• 3:25
  Speaker 1: the doctor, if it's time or not, and I want
• 3:27
  Speaker 1: to use data to do that. Yeah. I imagine I
• 3:30
  Speaker 1: frustrate a lot of doctors because I'm one of those
• 3:33
  Speaker 1: obnoxious people that goes in and it's like, well, here's
• 3:36
  Speaker 1: what I think I have based on my research. There's
• 3:39
  Speaker 1: nothing wrong with that. Yeah, that is what you're an
• 3:42
  Speaker 1: informed patient. That's true, exactly what you're supposed to do.
• 3:44
  Speaker 1: And if you're getting on your doctor's nerves, then go
• 3:47
  Speaker 1: see another doctor. Uh yeah, I agree. Actually in search
• 3:51
  Speaker 1: of a new GP right now for those because and
• 3:53
  Speaker 1: others you got on his nerves. Other reasons too, really
• 3:58
  Speaker 1: cold cold hands now like poor bedside manner, never seen
• 4:01
  Speaker 1: the doctor Like here's my intern from Emory. Yeah, which great.
• 4:06
  Speaker 1: You know. I love them getting experienced, but I would
• 4:09
  Speaker 1: like them both to be in there, not just like
• 4:11
  Speaker 1: smell you later and the doctor leaves. Well that's another
• 4:14
  Speaker 1: thing too. It's kind of like, um, doctor, okay, let's
• 4:18
  Speaker 1: let's just lay it on on the table here. What
• 4:20
  Speaker 1: what you've just mentioned and what I was talking about,
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  Speaker 1: if you put it all together. The medical field, physicians
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  Speaker 1: in particular, are currently in a what's the beginning of
• 4:31
  Speaker 1: what's possibly a really pickle of a state for them.
• 4:36
  Speaker 1: I think a transition period, yes, but they may be
• 4:38
  Speaker 1: transitioned right out of existence in large parts. Yes, I
• 4:41
  Speaker 1: may for sure, depending on who you talk to. There's
• 4:44
  Speaker 1: like this whole question now, like, what is the future
• 4:47
  Speaker 1: of medicine, and more specifically, in the case of this
• 4:51
  Speaker 1: episode that we're talking about, do human physicians factor largely
• 4:56
  Speaker 1: into that future? And the answer is no, yeah, depending
• 5:02
  Speaker 1: on who you ask, Like I said, um, we there's
• 5:04
  Speaker 1: this one guy, Dr Kent Bottles, who um, he feels
• 5:09
  Speaker 1: that GPS might go the way of the Dodo and
• 5:13
  Speaker 1: be replaced by diagnostic computers, maybe with avatars. Then there's
• 5:19
  Speaker 1: other people like farhad Manjou is a technical writer, his
• 5:22
  Speaker 1: wife as a pathologist. He thinks, no, no, no, the
• 5:25
  Speaker 1: GPS are the ones that are going to be in business.
• 5:27
  Speaker 1: The specialists are gonna be out of business because computers
• 5:30
  Speaker 1: are really good at specializing on one single thing, not
• 5:33
  Speaker 1: maybe so good at a general practitioner thing. So there's
• 5:38
  Speaker 1: lots of opinions out there on how much they'll be
• 5:40
  Speaker 1: replaced and who might be replaced. Right then, as a
• 5:43
  Speaker 1: reclient wrote a column who basically he basically said like now, like,
• 5:48
  Speaker 1: we we will still need humans, but we mainly need
• 5:51
  Speaker 1: humans to communicate to the other humans and facilitate the
• 5:55
  Speaker 1: the interaction between the robots and the humans, and we
• 5:57
  Speaker 1: already have this. They're called nurses or a nurse practitioners.
• 6:01
  Speaker 1: He kind of as reclined, is the one that thought
• 6:03
  Speaker 1: that a computer avatar might have a better bedside manner
• 6:07
  Speaker 1: than a doctor. Well, let's give that one example. There's this,
• 6:10
  Speaker 1: there was there's an example I kept finding while we
• 6:12
  Speaker 1: were doing research for this, and it's actually in the
• 6:14
  Speaker 1: article on how stuff works. Um, it's uh. There was
• 6:18
  Speaker 1: a kiosk, a medical kiosk, during a panel called man
• 6:22
  Speaker 1: Made Minds colon Living with Thinking Machines. When there's a
• 6:26
  Speaker 1: colon in there, you know it's serious stuff. Um. And
• 6:29
  Speaker 1: it was at the World Science Festival in two thousand
• 6:31
  Speaker 1: and eleven. And basically, this, this computerized avatar um interacted
• 6:36
  Speaker 1: with a woman whose baby had diarrhea, and the woman said, hey, Avatar,
• 6:42
  Speaker 1: my baby has diarrhea. What are you going to do
• 6:44
  Speaker 1: about it? And the avatar said, well, tell me all
• 6:47
  Speaker 1: the symptoms and all this stuff, and avatar decided that
• 6:50
  Speaker 1: the baby's diarrhea, while present, wasn't severe enough to warrant
• 6:55
  Speaker 1: immediate medical attention, so it went ahead and made an
• 6:58
  Speaker 1: appointment with a hue and doctor for later on that week,
• 7:02
  Speaker 1: and the mother said that she preferred the treatment by
• 7:06
  Speaker 1: the avatar to the real life nurses at the hospitals
• 7:10
  Speaker 1: where she lived in New York. Yeah. Uh so it
• 7:13
  Speaker 1: is possible to create computers with better bedside manner than say,
• 7:18
  Speaker 1: your g P. Well, it's at the very least it
• 7:21
  Speaker 1: will be consistent. And that's one of the things that
• 7:24
  Speaker 1: I'm not poopooing. Doctors or nurses are many, many, many,
• 7:27
  Speaker 1: many great ones, but I've also had some pretty bad
• 7:29
  Speaker 1: experiences in emergency rooms and with doctors and nurses. With
• 7:33
  Speaker 1: a computer, at least it's a consistent you know, their
• 7:36
  Speaker 1: program to display empathy no matter what. You know, they're
• 7:40
  Speaker 1: not too busy and they're not, you know, having a
• 7:43
  Speaker 1: bad day, so they don't you know, they don't have
• 7:46
  Speaker 1: any prejudices against you personally or anything like that. Their computer.
• 7:50
  Speaker 1: They don't hate diarrhea. But humans, humans respond to even
• 7:55
  Speaker 1: programmed empathy, even synthetic empathy from a a computer. I
• 8:01
  Speaker 1: could see that a little bit. Like I've dove into
• 8:05
  Speaker 1: the gaming world enough to know that, you know, the
• 8:10
  Speaker 1: realism of a of a avatar can be convincing, and
• 8:14
  Speaker 1: it's not like you think, oh, it's a real person,
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  Speaker 1: but it helps to put a human face on it,
• 8:17
  Speaker 1: you know, exactly. Literally, Um, they I saw a reference
• 8:22
  Speaker 1: to a study that found um, people who are being
• 8:25
  Speaker 1: treated for anxiety disorders tended to share more about their
• 8:30
  Speaker 1: experiences and themselves with an avatar them with a human psychiatrists.
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  Speaker 1: Oh that's interesting because they're like not embarrassed to tell
• 8:39
  Speaker 1: a real person. Yeah, that makes sense, I might open
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  Speaker 1: up more to to a computer. Right, So so we've
• 8:44
  Speaker 1: got that part, like the bedside manner. It is possible
• 8:47
  Speaker 1: that we can create machines now and are creating machines
• 8:50
  Speaker 1: now that have at least equal, if not better bedside
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  Speaker 1: manner than some physicians. Yeah, okay, so bedside manner one
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  Speaker 1: of the big things that doctors bring to the table.
• 9:00
  Speaker 1: Check computers have that. Yeah, it's it's different now than
• 9:04
  Speaker 1: it was in the old days. I feel like just
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  Speaker 1: the whole quality of personal care is gone down. It's
• 9:10
  Speaker 1: not necessarily the doctor's falter. There's a lot of reasons
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  Speaker 1: to place the blame. But it's not like when you
• 9:15
  Speaker 1: were a kid and you feel like you had your
• 9:16
  Speaker 1: family doctor who knew you, maybe even gave birth birth
• 9:21
  Speaker 1: you're my son exactly. Um, it just invested like you
• 9:27
  Speaker 1: gotta stick with the same doctor if you want that
• 9:28
  Speaker 1: kind of care, I think, right. And there's another benefit
• 9:31
  Speaker 1: besides bedside banner UM that comes with that that kind
• 9:35
  Speaker 1: of care, that kind of personal care is an awareness
• 9:38
  Speaker 1: of your medical history. Yeah, not just that, but oh well,
• 9:42
  Speaker 1: your dad died of congenital heart disorders like that, so
• 9:46
  Speaker 1: you may be at higher risk of it. To just
• 9:48
  Speaker 1: that kind of awareness has been typically lost to even
• 9:53
  Speaker 1: though we have medical histories and they're in our charts
• 9:54
  Speaker 1: that they're in our files UM, and intimate knowledge of
• 9:58
  Speaker 1: a patients UM medical history is pretty much lost in
• 10:04
  Speaker 1: today's modern practice of medicine. Yeah. UM. That's another thing
• 10:08
  Speaker 1: that that computers could conceivably top doctors on UM, which
• 10:14
  Speaker 1: basically falls under the umbrella of diagnosis or diagnostics. Yeah.
• 10:19
  Speaker 1: I mean there's two two sides to this. There's diagnoses
• 10:21
  Speaker 1: and treatment and some UH programs. A little bit of
• 10:26
  Speaker 1: the history this UM goes back to the nineteen seventies.
• 10:30
  Speaker 1: At the University of Pittsburgh, they develop software to diagnose problems. UM.
• 10:36
  Speaker 1: MASS General since the eighties has been working on their
• 10:39
  Speaker 1: d X plan, which provides ranked list of diagnoses. Whereas
• 10:45
  Speaker 1: the what's the computer the M Watson Watson who who
• 10:49
  Speaker 1: won at jeopardy. Yeah, that's more based. Um, it looks
• 10:52
  Speaker 1: like on treatment options than diagnosis at this point. So
• 10:56
  Speaker 1: they're using these well yeah, but they said it's not
• 10:59
  Speaker 1: they haven't. I don't think they want to leave it
• 11:01
  Speaker 1: alone with diagnosis yet. No, and to do its thing.
• 11:04
  Speaker 1: There's already something out there for diagnosis that's meant to
• 11:08
  Speaker 1: support physicians. From what I understand with Watson, if there
• 11:14
  Speaker 1: is a doctor of the future, it's Watson. Um. He
• 11:19
  Speaker 1: has a lot of advantages over not just um human doctors,
• 11:22
  Speaker 1: but other artificial intelligence healthcare machines. I guess you could
• 11:29
  Speaker 1: clumsily call it. He has a knack for natural language.
• 11:33
  Speaker 1: So let's say there's like a structured formula or formulaic
• 11:39
  Speaker 1: type of language that the medical field is supposed to use, right, yes, okay, Um,
• 11:47
  Speaker 1: health records don't always necessarily contain that language. They might
• 11:51
  Speaker 1: contain natural language, which is really confusing for computers to
• 11:55
  Speaker 1: take in an absorb. Yeah, you know, the humans can
• 12:00
  Speaker 1: pick up on meanings of things that robots and and
• 12:03
  Speaker 1: software cannot, like inferences, and we might be using sarcasm,
• 12:08
  Speaker 1: although there's probably not going to be any sarcasm in
• 12:11
  Speaker 1: your medical records. Yeah, but like figurative language and stuff
• 12:13
  Speaker 1: like that, but computers a language is a big part
• 12:16
  Speaker 1: of the problem. Or more to the point, with the diagnosis,
• 12:20
  Speaker 1: patient says he feels like he has a hive of
• 12:22
  Speaker 1: bees in his stomach, Like that might mean something that
• 12:27
  Speaker 1: you or me, but to a computer it's like followed
• 12:30
  Speaker 1: a bunch of bees or something. Right, Watson has the
• 12:32
  Speaker 1: advantage of saying, Okay, well, there's a sensation of bees
• 12:36
  Speaker 1: in the stomach, there's not actually bees in the stomach,
• 12:38
  Speaker 1: So let's figure this out then, Watson, or anything that
• 12:42
  Speaker 1: that he eventually becomes UM, well, we'll be able to
• 12:47
  Speaker 1: go through medical records, current medical research, UM, the patient's
• 12:52
  Speaker 1: medical history, UH, diagnostic tests that were done, blood work, UM,
• 12:57
  Speaker 1: instrument tests, and put it all together there and then
• 13:01
  Speaker 1: spit out a list of diagnoses with different confidence levels.
• 13:06
  Speaker 1: So the one at the top is the one that
• 13:07
  Speaker 1: Watson says is he is ninety eight point seven percent
• 13:12
  Speaker 1: sure is what's wrong with this patient? And UM as
• 13:17
  Speaker 1: a diagnostician, that's pretty impressive, and that's using all the
• 13:21
  Speaker 1: available data that's that's available also to human physicians, but
• 13:26
  Speaker 1: they simply don't have the time to take it all
• 13:30
  Speaker 1: in Yeah. I think some research said that eighty per
• 13:34
  Speaker 1: of doctors spend less than five hours a week reading
• 13:37
  Speaker 1: medical journals a month a month. Yeah, so that's these
• 13:42
  Speaker 1: things can read thousands in seconds. So it's it's sort
• 13:46
  Speaker 1: of a matter of of efficiency really, and like if
• 13:50
  Speaker 1: doctors don't have time to read all this stuff, I know,
• 13:53
  Speaker 1: we we looked into this one sort of a savant
• 13:56
  Speaker 1: diagnoser is that a word? I don't gnostician? Diagnostician? Uh
• 14:02
  Speaker 1: doctor uh Dolly Wall in San Francisco. He's sort of
• 14:06
  Speaker 1: legendary for diagnosing things, to the point where he does
• 14:10
  Speaker 1: it on stage as almost like a parlor trick. I
• 14:12
  Speaker 1: would love to see it. I would too. They give
• 14:14
  Speaker 1: him forty five minutes and and a bunch of symptoms
• 14:18
  Speaker 1: basically like really confusing because they're trying to stump him,
• 14:22
  Speaker 1: and generally he comes out on top. But he even
• 14:26
  Speaker 1: uses a program, a diagnostic program called isabel Right, that's
• 14:29
  Speaker 1: the one I said earlier, that's already here. Yeah, so
• 14:32
  Speaker 1: doctors are using these to help themselves out. But he
• 14:35
  Speaker 1: says that he's never had Isabelle offered diagnosis that he
• 14:39
  Speaker 1: has missed, but he's like the dude, Yeah, and He
• 14:43
  Speaker 1: also admits that he's like, like, I'm a freak of nature, right,
• 14:46
  Speaker 1: go ahead, quiz me exactly. Yeah. He also reads like
• 14:49
  Speaker 1: case histories, like for fun, that kind of stuff. He's not,
• 14:53
  Speaker 1: he's not a normal physician. He's a complete and total outlier. Um,
• 14:58
  Speaker 1: if he were, if every physician we're like this guy,
• 15:01
  Speaker 1: then they're there. Probably wouldn't be this conversation going on
• 15:05
  Speaker 1: right now. But most physicians aren't. And it's not just
• 15:09
  Speaker 1: with current medical research that they're just not aware of
• 15:12
  Speaker 1: because they haven't had time to pick up the lance
• 15:13
  Speaker 1: at the last few months, but it's also their training
• 15:16
  Speaker 1: to Like if a doctors in practice for twenty years,
• 15:19
  Speaker 1: the brain and the human brain tends to create habits
• 15:23
  Speaker 1: because it likes to expend as little energy as possible.
• 15:26
  Speaker 1: It's it's trying to be as ficient as possible. And
• 15:29
  Speaker 1: I think the same thing happens with medical practice. You're trained,
• 15:32
  Speaker 1: you understand, you come out of medical school with a
• 15:35
  Speaker 1: lot of book learning, and then you put it to
• 15:37
  Speaker 1: practice and you kind of find your niche and along
• 15:40
  Speaker 1: the way you forget a lot of the stuff that
• 15:41
  Speaker 1: you haven't done in twenty years or haven't learned about
• 15:43
  Speaker 1: in twenty years, so it's not just current stuff, it's
• 15:46
  Speaker 1: old stuff too. And if you feed the physician's desk
• 15:49
  Speaker 1: reference into Watson or one of his his compatriots, like,
• 15:53
  Speaker 1: all of that knowledge can be quickly index in research
• 15:56
  Speaker 1: to try to spit out a more accurate diagnosed. Yeah.
• 16:00
  Speaker 1: I think that's a great idea. It's like a partnering
• 16:03
  Speaker 1: up with computers. It is sarily replacing, but what they're
• 16:08
  Speaker 1: doing with Watson is is very much moving towards replacing
• 16:11
  Speaker 1: doctors in that sense. Well, here's a scary stat um.
• 16:14
  Speaker 1: One in five diagnoses in the United States are incorrect
• 16:16
  Speaker 1: or incomplete one in five and a lot of times
• 16:21
  Speaker 1: it's not that the doctor is a jerk or not
• 16:23
  Speaker 1: any good, but like you said, they just maybe haven't
• 16:26
  Speaker 1: seen these cases that were written about in some obscure
• 16:30
  Speaker 1: medical journal that the computer has scanned an index, you know.
• 16:33
  Speaker 1: And Dolly Wall Dr Dolly Wall himself at Freak Diagnostician Dollywood, Yeah,
• 16:39
  Speaker 1: pretty close, which is a wonderful place, by the way,
• 16:41
  Speaker 1: I know you love Dollywood. Um. Dr Dolly wall Uh
• 16:45
  Speaker 1: himself says a lot even with me, A lot of
• 16:49
  Speaker 1: it is intuition, and intuition can be wrong. That's a
• 16:53
  Speaker 1: criticism though, of computers as doctors. They lack intuition. Like,
• 16:59
  Speaker 1: there's kind of even larger, even larger than this computer's
• 17:03
  Speaker 1: replacing doctor's conversation going on. It's kind of a conversation
• 17:08
  Speaker 1: or a debate over whether intuition or data. Yeah, trump's
• 17:12
  Speaker 1: one or the other. Which one is the right way
• 17:15
  Speaker 1: to go? Yeah? This one stat too, it says according
• 17:19
  Speaker 1: to an expert, I'm not sure what that means. It
• 17:21
  Speaker 1: sounds sinky, but they said, only of the knowledge of
• 17:24
  Speaker 1: physicians use to diagnose is evidence based, So that means
• 17:30
  Speaker 1: is intuition, which which also jibs and dovetails with that
• 17:33
  Speaker 1: one in five being wrong, I mean, or one in
• 17:37
  Speaker 1: five being right. I'd like the idea of intuition to
• 17:40
  Speaker 1: a certain degree for sure, but there's also got to
• 17:42
  Speaker 1: be like data backing it up. Sure, you know, so
• 17:47
  Speaker 1: in your perfect world. And it sounds like we still
• 17:49
  Speaker 1: have physicians, but they go back and double check themselves
• 17:52
  Speaker 1: using a program. Yeah, but I could also be down
• 17:56
  Speaker 1: with um simple what is it? What do they call
• 17:59
  Speaker 1: it here? Um? Something based diseases, rules based chronic diseases. Yeah,
• 18:08
  Speaker 1: like minor things that are pretty easy to diagnose. They're
• 18:11
  Speaker 1: not even necessarily minor. We just understand them so fully
• 18:14
  Speaker 1: that we say type two diabetes is going to behave
• 18:17
  Speaker 1: and present itself like this. Yeah, but I wouldn't mind
• 18:19
  Speaker 1: going like it seems like once a year I get
• 18:22
  Speaker 1: like an upper respiratory infection. It's been three or four
• 18:24
  Speaker 1: years in a row, and I know what the treatment is,
• 18:27
  Speaker 1: I know how it feels. It would be great to
• 18:29
  Speaker 1: go into a machine and have them take some stats
• 18:33
  Speaker 1: and blow into it and hear my wheezing and give
• 18:36
  Speaker 1: me a a steroid shot and a Z pack and
• 18:41
  Speaker 1: a breathing treatment and send me on my way. So
• 18:43
  Speaker 1: it's always what clears it up. Would you care if
• 18:45
  Speaker 1: it was a robot that gave you that shot? Not
• 18:48
  Speaker 1: at all, um, but I definitely would want more personal
• 18:53
  Speaker 1: care if it was something what if it was a
• 18:54
  Speaker 1: robot with a nice avatar, sexy avatar maybe or just
• 18:59
  Speaker 1: a friendly one. Yeah, that was a little, a little,
• 19:01
  Speaker 1: a little it would touch your forearm here there. Yeah,
• 19:04
  Speaker 1: well that might be a little creepy. Yeah, if like
• 19:07
  Speaker 1: it was an old timey doctor who like gave you
• 19:09
  Speaker 1: some epocac if you had diarrhea, just send you on
• 19:12
  Speaker 1: your way drink a coke, but it wouldn't send you
• 19:14
  Speaker 1: on your way to give you ipocac and then it
• 19:16
  Speaker 1: wouldn't let go of your forearm. Yeah, so strong well
• 19:20
  Speaker 1: surgical robots. That's a that's a thing. I mean, we're
• 19:22
  Speaker 1: kidding around, but they've been performing. They've been performing robotic
• 19:27
  Speaker 1: surgery since the early eighties, um doctor assisted until two
• 19:32
  Speaker 1: thousand ten, where they were in Montreal. They performed the
• 19:35
  Speaker 1: first fully robotic surgeries when they removed a prostate with
• 19:40
  Speaker 1: a fully robotic UH surgeon and fully robotic anesthesiologist Dr
• 19:47
  Speaker 1: mc sleepy. Dr mc sleepy. Yeah, and the the that's
• 19:50
  Speaker 1: the real name the robot surgeon was da Vinci, which
• 19:52
  Speaker 1: is like the basically gold standard for robotic surgical or
• 19:57
  Speaker 1: surgical robots. Yeah, they had to that thirty thousand robotic
• 20:03
  Speaker 1: surgeries performed in the US, So it's it's big, it
• 20:06
  Speaker 1: is and um but the da Vinci is a doctor
• 20:10
  Speaker 1: basically sitting in a little uh it looks like an
• 20:13
  Speaker 1: arcade game and using UM robotic arms to mimic his
• 20:19
  Speaker 1: or her movements on more microscopic levels. Right, So the
• 20:23
  Speaker 1: robot has more precise movements and can make smaller movements,
• 20:27
  Speaker 1: um than the doctor. It's tell it's and what's the
• 20:30
  Speaker 1: opposite of telescoping, like going downward in scale? Whatever that is.
• 20:35
  Speaker 1: It's taking the movements of the doctor and reducing them
• 20:38
  Speaker 1: in scale. Let's call it reverse telescoping, reverse telescoping those movements, um,
• 20:43
  Speaker 1: which is a pretty awesome achievement in and of itself.
• 20:46
  Speaker 1: That doctors being fed three d um graphics of what
• 20:51
  Speaker 1: the robot is seeing, uh, and just kind of working
• 20:54
  Speaker 1: from there. Uh. What we're moving towards apparently is fully
• 21:01
  Speaker 1: robotic size surgeries. I was talking to Joe McCormick from
• 21:04
  Speaker 1: Forward Thinking and he was saying that, um, there was
• 21:09
  Speaker 1: there's something called the Raven four, I believe. Uh. And
• 21:13
  Speaker 1: basically you just say, this is going to be a
• 21:15
  Speaker 1: gall bladder surgery on a six ft six male age
• 21:20
  Speaker 1: you know whatever. And here's his here's the cat scan
• 21:24
  Speaker 1: of his abdomen um. So go removes gall bladder and
• 21:28
  Speaker 1: you press enter and the thing goes in there and
• 21:31
  Speaker 1: like removes the guy's gall bladder and sews him up. Yeah,
• 21:34
  Speaker 1: that's fully robotic, like fully autonomous robotic surgery. Button then
• 21:40
  Speaker 1: it does it. You're not actually controlling a machine that
• 21:42
  Speaker 1: does it exactly the machines doing it at your behest,
• 21:46
  Speaker 1: but you're not controlling it. Yeah. Um, and we're right
• 21:49
  Speaker 1: on the cusp of that, and apparently it's already happening.
• 21:52
  Speaker 1: Uh yeah, but there are some issues. UM. I looked
• 21:55
  Speaker 1: into it and found that a lot of injury reporting
• 21:59
  Speaker 1: and robotics agery is um not being reported. It's it's substandard.
• 22:04
  Speaker 1: And uh, this woman, Sheina Wilson, had robotic surgery for
• 22:08
  Speaker 1: hysterectomy in two thousand thirteen and apparently this uh intuitive
• 22:13
  Speaker 1: surgical system had there had been a bunch of injuries
• 22:18
  Speaker 1: that she didn't know about, and she had her rectum
• 22:20
  Speaker 1: burned badly and said, if I would have known that
• 22:24
  Speaker 1: this system had these issues, would not have elected to
• 22:28
  Speaker 1: take part in it. So there's a lot of under reporting. Um.
• 22:31
  Speaker 1: The f d A, UM, they have no authority to
• 22:35
  Speaker 1: force a doctor to do this, and apparently there's every
• 22:38
  Speaker 1: reason in every link in the chain not to report
• 22:42
  Speaker 1: these things, you know, and the f d A not
• 22:46
  Speaker 1: enforcing this kind of thing, not enforcing reporting is ridiculous. Yeah.
• 22:51
  Speaker 1: You know. The thing is that things like that happen,
• 22:54
  Speaker 1: and there's under reporting. UM. With human surgic surgeons as well. Yeah, sure,
• 23:00
  Speaker 1: not just robotic. It's like overall, apparently surgical injury and
• 23:04
  Speaker 1: accident reporting is not compulsory. Yeah, and here's here's a
• 23:08
  Speaker 1: few points though. Counterpoints I guess is one, it's not
• 23:11
  Speaker 1: always the robotic component of the surgery that was the
• 23:15
  Speaker 1: cause to a lot of times they say they don't
• 23:18
  Speaker 1: know about this until like a lawsuit is filed, So
• 23:22
  Speaker 1: it could be weeks or months later with the physician
• 23:24
  Speaker 1: doesn't know about it, or the FDA might not get
• 23:27
  Speaker 1: report on it, and like six months later you follow
• 23:30
  Speaker 1: a lawsuit and that's how it comes to light. Um.
• 23:32
  Speaker 1: But the FDA is definitely concerned and are supposedly working
• 23:35
  Speaker 1: to improve this. That's very concerned. They're very concerned. Uh.
• 23:41
  Speaker 1: And another problem too, and that same article, a lot
• 23:43
  Speaker 1: of these robotic surgical systems, you still have to have
• 23:48
  Speaker 1: the correct amount of training. And Uh. The feeling of
• 23:51
  Speaker 1: some experts is that UM or at least this one guy,
• 23:55
  Speaker 1: Enrico Benedetti, he's a head of surgery at the University
• 23:58
  Speaker 1: of Illinois Chicago, UH, says a lot of it just
• 24:01
  Speaker 1: comes back to training. These some of these doctors aren't
• 24:03
  Speaker 1: getting adequately trained in these machines enough to perform this regery. Yeah,
• 24:07
  Speaker 1: like what happens when I do this? Oh? That happens.
• 24:12
  Speaker 1: That's not good. I've got another alarming stat for you
• 24:15
  Speaker 1: to hold on. Hold on, hold on. Before that, let's
• 24:18
  Speaker 1: do a message break real quick. Okay, tell me your
• 24:37
  Speaker 1: alarming stat al right. JOHNS. Hopkinsider a study that found
• 24:40
  Speaker 1: as many as forty thou patients die in intensive care
• 24:44
  Speaker 1: each year in the US due to misdiagnosis man and UM.
• 24:49
  Speaker 1: Another study found that system related factors like UH, lack
• 24:53
  Speaker 1: of teamworking, communication, or just poor processes were involved in
• 24:57
  Speaker 1: six of diagnostic error and cognitive factors, and with premature
• 25:04
  Speaker 1: closure is the most common, which is basically just sticking
• 25:08
  Speaker 1: to that initial diagnosis and not being open minded to
• 25:10
  Speaker 1: other like second opinions. Yeah. So there's this thing called
• 25:14
  Speaker 1: anchoring bias that UM was in that New York Times article.
• 25:18
  Speaker 1: Dr Dolly Wall the guy who created this program that's
• 25:21
  Speaker 1: now around to support diagnostics where a physician will say,
• 25:26
  Speaker 1: I think it's this, but let me put in the
• 25:28
  Speaker 1: symptoms and ask Isabelle Um which is the name of
• 25:31
  Speaker 1: the program, and it's named after the guy who created
• 25:33
  Speaker 1: the program's daughter. Yeah, when she was three, took her
• 25:38
  Speaker 1: to the hospital and the doctors said, well, she has
• 25:40
  Speaker 1: chicken pox. And she did indeed have chicken pox, but
• 25:43
  Speaker 1: that's all they looked at. They completely missed a pretty
• 25:46
  Speaker 1: nasty case of necrotizing fasciitis, which we've talked about before,
• 25:50
  Speaker 1: flesh eating bacteria, and um, she almost died from it.
• 25:54
  Speaker 1: It was. It was disfigured from it as a result,
• 25:57
  Speaker 1: so that her father, who was a money manager, said,
• 26:00
  Speaker 1: I'm going to take whatever computer programming skills I haven't
• 26:03
  Speaker 1: put it towards this program Isabelle, which is meant to say, yes,
• 26:08
  Speaker 1: you're right with this diagnosis, I agree with you, or
• 26:11
  Speaker 1: have you considered these other diagnoses? And he said, like,
• 26:14
  Speaker 1: had hasabel been around and his daughter's doctors consulted it,
• 26:18
  Speaker 1: they would not have missed the necrotizing fasciitus. Well, it
• 26:21
  Speaker 1: makes sense, um as an assist. You know. Um, there's
• 26:24
  Speaker 1: this company called Life Calm that said in clinical trials
• 26:27
  Speaker 1: that if you use a medical diagnostic program as an assist, Uh,
• 26:32
  Speaker 1: those engines were accurate without using exams or imaging or
• 26:37
  Speaker 1: labs even really just symptoms. Yeah, that's crazy, that's really
• 26:44
  Speaker 1: really really good. Yeah, like that's a that's an A,
• 26:48
  Speaker 1: that's a low A. It's still in a. But as
• 26:51
  Speaker 1: an assistant, I think it's you know, it's kind of
• 26:53
  Speaker 1: a no brainer, don't you think. Oh yeah, I think so.
• 26:57
  Speaker 1: I don't know why. I all I can think of
• 27:00
  Speaker 1: is possibly worrying about feeding the beasts that will take
• 27:05
  Speaker 1: your job, or just having too much of a case
• 27:08
  Speaker 1: load to take the time to double check your work
• 27:11
  Speaker 1: on a computer would be the only reasons why doctors
• 27:15
  Speaker 1: aren't using that. Well, the smartphone is becoming a potential
• 27:19
  Speaker 1: uh self diagnos ur There's all these cool things on
• 27:23
  Speaker 1: the horizon that you can use your your phone for.
• 27:27
  Speaker 1: There's one called a live Core which you can take
• 27:29
  Speaker 1: your own ECG testy and potentially, for the cost of
• 27:33
  Speaker 1: getting one e c G in a hospital, you could
• 27:36
  Speaker 1: send a year's worth of daily ECGs you took yourself
• 27:40
  Speaker 1: to your doctor, and then you carry all that info
• 27:44
  Speaker 1: and all of your other medical info from all of
• 27:46
  Speaker 1: your apps that will eventually be integrated into one or
• 27:48
  Speaker 1: two apps that will probably become preloaded on your iPhone
• 27:51
  Speaker 1: in the next couple of years. And you've got your
• 27:53
  Speaker 1: medical history right there. Yeah, and I you know, most
• 27:56
  Speaker 1: of these require like a little clip on like um,
• 27:59
  Speaker 1: something called cell scope that's like you clip it onto
• 28:02
  Speaker 1: your little camera lens essentially, and it's like, what are
• 28:06
  Speaker 1: the little magnifiers with the lights that doctors used to
• 28:08
  Speaker 1: look in your ears and eyes? Uh, yeah, it looks
• 28:11
  Speaker 1: like one of those clipped onto your your iPhone and
• 28:14
  Speaker 1: it produces, uh, you can do imaging for skin moles
• 28:17
  Speaker 1: and rashes and ear infections. They have one called NTRA
• 28:22
  Speaker 1: that you could potentially give your own eyes uh, get
• 28:26
  Speaker 1: your own like glasses prescription done and then you ordering
• 28:31
  Speaker 1: the information to some website and they say and then
• 28:35
  Speaker 1: this one called Adamant that smells your breath, that smells
• 28:41
  Speaker 1: gases in your breath and it could detect like lung
• 28:44
  Speaker 1: cancer even yeah, apparently you have real metabolic changes to
• 28:49
  Speaker 1: the smell of your breath yea when you have different
• 28:52
  Speaker 1: types of cancer, not just long um. Like bees can
• 28:55
  Speaker 1: detect breast cancer. Um. If you breathe into like this
• 29:00
  Speaker 1: special glass fear with bees around it, they can be
• 29:02
  Speaker 1: trained to detect lung cancer and they come back with
• 29:05
  Speaker 1: the correct results a lot of the time. So a
• 29:08
  Speaker 1: lot of these are on the horizon they're not like
• 29:10
  Speaker 1: in heavy rotation yet, No, but but it's pretty neat
• 29:13
  Speaker 1: All of them reveal this idea that no one cares
• 29:17
  Speaker 1: about your particular health and well being more than you.
• 29:22
  Speaker 1: Unless you're one of those dudes who doesn't really care.
• 29:25
  Speaker 1: Then your your wife does or your mom you know,
• 29:29
  Speaker 1: and we probably cares more about me than me, right,
• 29:31
  Speaker 1: But there's there. The point is the doctor, the insurance company,
• 29:36
  Speaker 1: the the hospital. While they're all in the field because
• 29:40
  Speaker 1: they do care about your health, of course, they can't
• 29:42
  Speaker 1: possibly care about it more than you or your loved
• 29:44
  Speaker 1: one does. So the idea of giving you the ability
• 29:48
  Speaker 1: to keep all of that information yourself and easily handed
• 29:51
  Speaker 1: over to them or potentially down the road, a computer
• 29:55
  Speaker 1: version of them. I can't think of any any better
• 29:58
  Speaker 1: revolution in medicine right now than that read. I think
• 30:01
  Speaker 1: it's pretty exciting. Yeah. I think we're going to live
• 30:03
  Speaker 1: into the triple digits, buddy. Yeah. And I think there
• 30:06
  Speaker 1: will always be a need for doctors and nurses. I
• 30:08
  Speaker 1: don't think anyone will be wholly replaced but a little
• 30:12
  Speaker 1: robot assist. Yeah. Yeah. Let me make one more point,
• 30:16
  Speaker 1: all right, there's so you've heard of genomics, Yes, There's
• 30:20
  Speaker 1: also this thing called proteonomics, which is basically your protein
• 30:24
  Speaker 1: version of your your genome, your genome, and it's all
• 30:27
  Speaker 1: of the proteins in your body that you have that
• 30:29
  Speaker 1: your manufacturing, that you're losing, and all the changes and
• 30:32
  Speaker 1: fluctuations in them. And the idea is that you can
• 30:35
  Speaker 1: get a full work up of your proteonome and your genome,
• 30:41
  Speaker 1: and eventually you can add that to your medical history
• 30:44
  Speaker 1: as well, what your E k G reading has been
• 30:46
  Speaker 1: over the past year, um, any way you may have
• 30:49
  Speaker 1: gained or lost or anything like that, what your breath
• 30:53
  Speaker 1: smells like metabolically speaking, and not only have your current
• 30:57
  Speaker 1: state of health, but personalized your version of that personalized
• 31:03
  Speaker 1: down to your genes and proteins in your body, so
• 31:07
  Speaker 1: a treatment could be specifically tailored to you. Wow, that's
• 31:12
  Speaker 1: gonna be really tough for a human physician to do
• 31:14
  Speaker 1: that on their own. To top that, Yeah, the the
• 31:17
  Speaker 1: amount of data available already is overwhelming human doctors. When
• 31:21
  Speaker 1: you add this other kind of stuff on it, it's
• 31:23
  Speaker 1: just pulling away from them more and more. Yeah, and
• 31:26
  Speaker 1: medical record keeping is uh, I know, there's been issues
• 31:29
  Speaker 1: with that and digitizing that and keeping up with medical records,
• 31:33
  Speaker 1: and if you could be yourself advocate and keep up
• 31:35
  Speaker 1: with your own medical records, it might be kind of nice.
• 31:38
  Speaker 1: So I I feel like we answered the question, which
• 31:42
  Speaker 1: is yes, no more doctors. I don't know. I think
• 31:46
  Speaker 1: in in the future, I will always have humans to
• 31:49
  Speaker 1: interact between us. I think because we're always gonna want
• 31:53
  Speaker 1: somebody to yell at or be like what is this
• 31:54
  Speaker 1: robot doing? Or can you help me this robots give
• 31:57
  Speaker 1: me some ipocacu and won't let go on my arm
• 31:59
  Speaker 1: or burn my rectum. Yes, we're always going to need humans.
• 32:04
  Speaker 1: It's just I don't know, well we need physicians, and
• 32:06
  Speaker 1: if we do, will they be super specialized like just
• 32:09
  Speaker 1: the Supreme Court of Physicians. Who knows. It's pretty exciting.
• 32:14
  Speaker 1: But we will see this change one way or another
• 32:16
  Speaker 1: in the next fifteen years under my prediction to it's happening. Okay,
• 32:22
  Speaker 1: goog and Chuck if the year yeah. Really, If you
• 32:26
  Speaker 1: wanna learn more about computers possibly replacing doctors, you can
• 32:31
  Speaker 1: type those words into the search bar how stuff works
• 32:33
  Speaker 1: dot com. And since I said search bar, that means
• 32:36
  Speaker 1: it's time for a message break. Okay, So, so what
• 32:55
  Speaker 1: do we have listener mail time. Yeah, I have one
• 33:01
  Speaker 1: called I'm gonna call it fight Club. Okay, hey guys,
• 33:05
  Speaker 1: just finished the podcast on deep refrigerating. I think I'll
• 33:09
  Speaker 1: keep my Energy Star certified fridge. Thanks very much. But
• 33:13
  Speaker 1: Josh did mention something about eating weeds and asked a
• 33:16
  Speaker 1: somewhat rhetorical question, what are weeds anyway? Just plants we
• 33:19
  Speaker 1: say are bad? It reminded me of some today's common
• 33:22
  Speaker 1: uh some that some of today's common noxious weeds. How
• 33:25
  Speaker 1: they got their reputation not so long ago, lawns were
• 33:28
  Speaker 1: perfect blends of Bermuda rye and Kentucky blue grass. They
• 33:32
  Speaker 1: also included many types of clover, dandelion, and other quote weeds.
• 33:35
  Speaker 1: In fact, many seed mixtures specifically included white clover because
• 33:38
  Speaker 1: it makes an excellent cover in soils where more common
• 33:41
  Speaker 1: grasses won't grow. In steps the Scott Fertilizer Company, post
• 33:44
  Speaker 1: World War Two America housing tracks were popping up all
• 33:47
  Speaker 1: over the US and new suburbia, and Scott was encouraging
• 33:50
  Speaker 1: returning gis to take pride in their new lawns and
• 33:52
  Speaker 1: to buy their products to do so. And we're extremely
• 33:55
  Speaker 1: high waisted pants, that's right. They produced fertilizers, weed killers,
• 33:59
  Speaker 1: and other long your products, some of which had a
• 34:01
  Speaker 1: curious side effect killing many leafy greens that came up
• 34:04
  Speaker 1: to the point that we're not considered weeds at the time,
• 34:07
  Speaker 1: including white clover. Instead of reformulating, what they did was
• 34:11
  Speaker 1: what any red blooded American corporation would do. They redefined
• 34:14
  Speaker 1: what was a weed. White clover made that list as
• 34:16
  Speaker 1: the dandelions, when in fact both are still in use
• 34:20
  Speaker 1: today in cooking and medicines. Would you call that a
• 34:22
  Speaker 1: noxious weed? No? So thanks for that, guys, and thanks
• 34:26
  Speaker 1: for all the knowledge I've learned and have a great
• 34:29
  Speaker 1: and that is from Robert Paulson. Oh yeah, Robert Paulson.
• 34:33
  Speaker 1: He's a he's a sharp dude. That's why I called
• 34:36
  Speaker 1: it fight club, remember that. Oh yeah, I think I
• 34:39
  Speaker 1: made a joke to him about that once on Twitter
• 34:41
  Speaker 1: and he never responded. Yeah, he's he writes in a
• 34:43
  Speaker 1: lot now he's every time I see his name, I
• 34:45
  Speaker 1: think and his name is Robert Paulson. Yeah, thanks a lot,
• 34:48
  Speaker 1: Robert Paulson. We appreciate you. If you ever shot in
• 34:51
  Speaker 1: the head and the commission of a robbery, we will
• 34:53
  Speaker 1: dispose of your body. Um. If you want to get
• 34:58
  Speaker 1: in touch with me and Chuck, and you have a
• 34:59
  Speaker 1: name that you would like us to poke fun at
• 35:02
  Speaker 1: Bring it On. You can tweet to us at s
• 35:05
  Speaker 1: y s K podcast. You can post your name on
• 35:08
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• 35:12
  Speaker 1: send us an email to stuff Podcasts at how stuff
• 35:14
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• 35:18
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• 35:21
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• 35:26
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• 35:29
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• 35:31
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• 35:34
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