Driving may reveal early signs of Alzheimer's
bbc.co.uk
bbc.co.uk
> All models were trained on 70% of the data and tested on the remaining 30% of the data. Note that each month record for each participant was considered an independent data point.
I'm almost certain that this is a mining leak.
Data from one patient will end up both in the training and test set and result in fantastic accuracy. Of course it will be from different months. The correct way to do this is to cross-validate/split across the population. It seems unlikely, from this description, that the authors have done so.
[1] https://alzres.biomedcentral.com/articles/10.1186/s13195-021...
It's a very common error and it should be easy to catch but....I've even seen a study that treated individual slices of an MRI as independent, which is laughably wrong.
I think part of the problem is that the "analysts" are increasingly uninvolved in the data collection, and just treat it as a tuple of (X, y). If you thought about what they mean, even for a second, ("Oh, Mr. Smith is always an awful driver"), the problem is obvious.
But this doesn't help you in the real world where you won't necessarily have near neighbors corresponding to the same person, with a known diagnosis.
Of course, we don't wait to try it on real patients, so typically you'd partition the data you have already into (a) what you show to the machine learner (training data), and (b) what you hide from the learner (test data). The latter is only used to evaluate, i.e. you get the answer from the ML model and compare it to the real answer you have already. If information about the test data some how makes it to the training data, its referred to as a mining leak [1].
In this paper, they treat each month of a patient as an independent observation. However, GPS driver behaviour will be very similar from one month to the next for the same person. Genetic information is exactly the same. So for every month that the model is tested (test data), the learner has already seen very similar data in the training set - for some of the other months (for the same person) that happen to be in the training set. The split is typically done randomly. So it will do well.
The test results are therefore optimistic and do not support the conclusions.
[1] https://en.wikipedia.org/wiki/Leakage_(machine_learning)
Specifically, those with preclinical Alzheimer's tended to drive more slowly, make abrupt changes, travel less at night, and logged fewer miles overall, for example. They also visited a smaller variety of destinations when driving, sticking to slightly more confined routes.
Everyone I know who gets older tends to drive less at night because as you get old your eyesight gets worse —- particularly if you’ve had cataract surgery, which are people who are in the study / risk group.
Unless I missed a more nuanced point this article reads like “old age is a good predictor of Alzheimer’s.”
If they're sitting at home, not driving anywhere, watching cable news all day, that's a recipe for rutted-grooves of thought and deterioration of the mind.
The interesting part for me here is that these behaviors do, in fact, reflect a neurological issue I have with visual/spatial processing. In a nutshell, I get lost easily, because it takes me much more time to associate visual landmarks with a travel route than the typical human. I suspect my dog has a far, far better sense of direction than do I. :P
I'm not even close to old enough to have preclinical signs of Alzheimer's, yet, but I shall have to remember to remind my doctors of my visual-spatial issues in a few decades when I am.
In particular, Driving from point A to point B depends on a certain kind of memory that degrades quickly in Alzheimer's. Forgetting names is one thing but forgetting whole places is another.
* Making abrupt changes: perhaps they are suddenly recalling something they need to do like turn onto a certain street? Not quite sure. * Driving at night removes a lot of visual cues putting an even larger emphasis on memory. * Longer travels & having more destinations both depend on memory so that one makes sense.
Cataract surgery should improve night vision. Those with cataracts generally have much worse night vision because their vision is clouded.
If night vision is worse, it could indicate that the person needs a follow up with their eye surgeon and possibly follow up surgery to adjust the IOL.
How about: "You weren't as good as you thought, and you just missed it when you were younger."
If you look at driving accidents, they fall continuously until you are about 30. And they don't start rising again until you are about 75-80.
Yes! A slow driver (under 50) can cause very high closing speeds for drivers who aren't paying attention. A likely accident scenario could be a driver who tailgates a white van that is itself closing fast on the slow vehicle, blocking the view of the tailgater (all are in the inside lane). If the van makes a late overtaking manoeuvre (to avoid the slow vehicle) rather than smoothly braking, the tailgater has very little time to react, and depending on traffic density, might not themselves be able to change lanes.
I saw this exact situation happen a few days ago. I was in lane 2 about 100m further back down the road. The van changed lanes at the last possible moment. The tailgater slammed on his brakes and came very close to shunting the slow vehicle. Luckily there was no-one behind him so a braking wave didn't propagate back down the lane.
What if the "slow driver" was a normal driver who just got a puncture and was slowing down?
If the slow car has an issue that makes it so that they cannot go any faster they should be putting their hazards on and slowing down, in which case it would be the drivers who are not paying attention's fault.
Really in both cases the drivers not paying attention share some of the blame, but in the first case the slow driver is also being irresponsible.
Then they'd have a good excuse.
Same with the shitbox running on 3cyl.
Same with the concrete truck that pretty much has to drive under the prevailing speed uphill because it's so slow.
To voluntarily create a hazard when you can "just not" by behaving like everyone else (which is not exactly an activity that requires a lot of cognitive thought) is simply asinine.
What happens is you wind up with a merge (and all the shenanigans that causes) behind the blockage and given a long enough duration you eventually run into the case someone doesn't check their mirrors/blind spot and hits someone who's not on their A-game because there's no exit there and they're not expecting the person to merge there.
Aside from the abrupt changes this could describe my driving habits. I hate driving, driving at night most of all.
I wonder what the direction of the causality is. Maybe there is something else that triggers the slow driving. Visiting the same destinations regularly instead of varying ones might also just point to a very routine lifestyle. Maybe that contributes to Alzheimer’s a lot? It feels a stretch to use these attributes as casuals for attribution of Alzheimer’s.
I suspect the arrow goes:
X -> brain degradation
brain degradation -> cognitive decline
cognitive decline -> driving bad
brain degradation -> post-mortem Alzheimers diagnosis
[0] The 90+ study: https://mind.uci.edu/research-studies/90plus-study/
60 Minutes on Superagers - Video + Transcript: https://www.cbsnews.com/news/long-life-retirement-community-...
This plasticity idea is really neat. Anecdotal and I don’t know the correlation holds up, but my one grandmother was very set in her habits and particularly mindset and died early of Alzheimer’s and Parkinson’s. My other grandmother is flexible of mind and is still kicking it at 90+.
I’m wondering which way the causality goes. Whether there is something physical which makes people more open minded and wandering whereas others are more closed which eventually leads to more brain diseases. So in the end the open mindedness / flexibility is just another indirect indicator.
There doesn't need to be a cure or treatment for companies to make money from it.
What do you think insurance, as a financial product, is? An entity looking to hedge against financial uncertainty relies on being placed in a cohort that represents equivalent risk profile to their own.
Right now, despite their best efforts, insurance companies are still fairly limited in their ability to discriminate and exclude certain swathes of people from access to affordable healthcare. Once they manage it, they become useless to us as a society.
Ideally, we as a society want all of our members to be able to see a doctor when they are sick or injured.
Ideally, insurance companies want to exclusively insure people to whom they will never need to pay out. They optimize their profit margin to be essentially 100%. Which then makes them a leech, and they're probably a leech well below 100% as well.
(To be fair, since the system is completely inhuman, individuals will also play the same game and try to leave the risk pool if they are sufficiently low-risk.)
So, there will come a time when we have to either give up any facade that we value human health intrinsically, or we must stop using private insurance as the primary method of ensuring it (no pun intended).