just make an app that warns you if any of you friends cell or computer use changes. I'd pay to see which of my friends might be getting sick. Luckily, each new health scare will drive up demand.
Ask YC: This is our tech, how can we make this into a product that people want?
11–20 of 31 posts
Re: Ask YC: This is our tech, how can we make this into a product that people want?
#12> When Madan trained software to hunt for this signature in the cellphone data, a daily check correctly identified flu victims 90 per cent of the time. I'm very surprised by this - it strikes me that I'd expect it to be hard to tell from such data that it wasn't a stomach upset, tiredness, onset of disease or simply a heavy cold. Indeed 90% sounds like it might be higher than correct identification via an interview w…
The 90% is a misquote, good catch.
The actual accuracy is between 60-90%, depending on clusters of symptoms, and apparently that was stripped somewhere during editing. Oh well.
Re: Ask YC: This is our tech, how can we make this into a product that people want?
#13I would market this to pharmaceuticals as a way to effectively gauge demand geography. The value added for them would be supply chain optimization.
good idea. we had an initial chat with one of the major ones. They'd like to see more traction of course.
Re: Ask YC: This is our tech, how can we make this into a product that people want?
#14Thoughts? We're thinking of individual-level prediction tools, but there are other ways of using this approach. e.g. at the community / city scale with mobile operator data.
Thought:
You might see if this could get funded as a means to help seriously at risk populations reduce their risk, spot problems at an earlier stage and so on.
I have a form of cystic fibrosis, as does my 23 year old son. We have gotten a great deal healthier than doctors claim is possible largely by making dietary and lifestyle changes to protect us from illness, rather than waiting until we are ill and loading up on drugs. I'm extremely controversial in the CF community. But if you had funding from some "kosher" organization (unlike me -- I'm just some loudmouthed individual speaking from firsthand experience...aka "fruitcake"), well, there is real potential to do real good here, not just for the individual quality of life but also the economy: By my estimation, the 30,000 or so people with CF in the US consume roughly $3billion+ annually (edit: I mean in medical care -- doctors visits, drugs, hospitalizations), most of which does not come out of their pockets. Most of it comes from insurance, state aid, federal aid, charities, and even medical write-offs when patients who are routinely deathly ill simply can't pay. I don't know how to tap into that $3 billion, but it is in someone's best interest monetarily (if nothing else) to help this population (and others like it) stay healthier. And I know it is an achievable goal because I do it every day. I just don't know how to adequately explain to other people how to do what I do.
I hope this goes somewhere. I am excited to see something like this. It fits nicely with my views on what works, health-wise.
Best of luck.
Re: Ask YC: This is our tech, how can we make this into a product that people want?
#15Interesting. Questions 1. How fast can you spot a trend? 2. How is the tracking working? 3. How precise is it. I could imagine traffic would be a good area to look into.
Trends are spotted in the first 48-hour window, in our sample. There is the big open question of validation outside the sample population of course.
By precise, do you mean precision versus recall? The tradeoff depends on what you want to do with the inferences. If you send the analysis to say a nurse or family member (i.e., human in the loop, which we think is the right approach) then recall should be optimized.
Re: Ask YC: This is our tech, how can we make this into a product that people want?
#16> When Madan trained software to hunt for this signature in the cellphone data, a daily check correctly identified flu victims 90 per cent of the time. I'm very surprised by this - it strikes me that I'd expect it to be hard to tell from such data that it wasn't a stomach upset, tiredness, onset of disease or simply a heavy cold. Indeed 90% sounds like it might be higher than correct identification via an interview w…
The 90% is a misquote, good catch. The actual accuracy is between 60-90%, depending on clusters of symptoms, and apparently that was stripped somewhere during editing. Oh well.
With a range that large, I would be highly suspect that when you did get 90%, it was just fitting the data. And how would you even confirm if they had the flu - even a doctor could misdiagnose mild flu, which adds more noise.
60% really means very little if it's a binary choice - flu or no. You'll be right 50% of the times no mater what.
Re: Ask YC: This is our tech, how can we make this into a product that people want?
#17Interesting. Questions 1. How fast can you spot a trend? 2. How is the tracking working? 3. How precise is it. I could imagine traffic would be a good area to look into.
>3. How precise is it.
I've just been away in the Midlands (UK) and used Google Maps on a mobile for the first time. The triangulation of position was only accurate to about 1500m radius and then would switch between positions quite often. Such info would look much like a user that was moving quite a lot - I expect it could be filtered out but this sort precision (and lack of accuracy) appears common in the UK.
Re: Ask YC: This is our tech, how can we make this into a product that people want?
#18Earlier quoted context omitted.
The 90% is a misquote, good catch. The actual accuracy is between 60-90%, depending on clusters of symptoms, and apparently that was stripped somewhere during editing. Oh well.
With a range that large, I would be highly suspect that when you did get 90%, it was just fitting the data. And how would you even confirm if they had the flu - even a doctor could misdiagnose mild flu, which adds more noise. 60% really means very little if it's a binary choice - flu or no. You'll be right 50% of the times no mater what.
>60% really means very little if it's a binary choice - flu or no. You'll be right 50% of the times no mater what.
What? Just because something is binary doesn't mean it happens half the time.
Re: Ask YC: This is our tech, how can we make this into a product that people want?
#19Thoughts? We're thinking of individual-level prediction tools, but there are other ways of using this approach. e.g. at the community / city scale with mobile operator data.
Thought: You might see if this could get funded as a means to help seriously at risk populations reduce their risk, spot problems at an earlier stage and so on. I have a form of cystic fibrosis, as does my 23 year old son. We have gotten a great deal healthier than doctors claim is possible largely by making dietary and lifestyle changes to protect us from illness, rather than waiting until we are ill and loading up…
Thanks for the kind words, and good luck to your family. We really do want to make this into a tool that can help people, if possible.
My intuition is that being able to quantify and visualize 'quality-of-life' automatically, will help support diet and lifestyle changes.
What kind of features/UI would you like to see in such a tool? Would it be better is this was generic (e.g. like Facebook), or something specifically for patients with CF?
Re: Ask YC: This is our tech, how can we make this into a product that people want?
#20Earlier quoted context omitted.
With a range that large, I would be highly suspect that when you did get 90%, it was just fitting the data. And how would you even confirm if they had the flu - even a doctor could misdiagnose mild flu, which adds more noise. 60% really means very little if it's a binary choice - flu or no. You'll be right 50% of the times no mater what.
>60% really means very little if it's a binary choice - flu or no. You'll be right 50% of the times no mater what. What? Just because something is binary doesn't mean it happens half the time.
Hmm, yeah... good point on that. I'll leave my comment, but I take it back :)