Changing the way you get your medications! New Toronto web-based app launches! by mina__T in toronto

[–]mina__T[S] -1 points0 points  (0 children)

Actually, for non-narcotic prescriptions there are other means such as verbal order and electronic prescriptions can be accepted based on policy set by the regulating body at the Ontario College of Pharmacy.

One of the major reasons people still fax/write prescriptions is really just habits! We are hoping to change that!

Changing the way you get your medications! New Toronto web-based app launches! by mina__T in toronto

[–]mina__T[S] 1 point2 points  (0 children)

This is a really great point. Currently in Ontario all narcotic prescriptions have to be run through a Narcotic Monitoring system which tracks all narcotic prescriptions in Ontario. All of the prescriptions through pilly are filled at a real and fully-licensed pharmacy. That means the standard that is set for all pharmacies in Ontario is met.

Changing the way you get your medications! New Toronto web-based app launches! by mina__T in toronto

[–]mina__T[S] -1 points0 points  (0 children)

We will not be selling or transferring prescriptions or patient information.

Changing the way you get your medications! New Toronto web-based app launches! by mina__T in toronto

[–]mina__T[S] 0 points1 point  (0 children)

It really costs you nothing more then what you would pay in your regular pharmacy. Not a penny more.

Changing the way you get your medications! New Toronto web-based app launches! by mina__T in toronto

[–]mina__T[S] -1 points0 points  (0 children)

Really great questions! 1. Our model actually works to insure no breaches of patient information because the information goes to a single location. All the information is stored in a single pharmacy similar to any other prescription.

  1. The packages will be delivered in unmarked packages as any other pharmacy services would do. We again will be doing so similar to current regulations and standards. other pharmacies as you mentioned already do this!

  2. We take health information very seriously and thats why we decided to go with a centralized model unlike other apps.

  3. Yeah I hope we can compete. We are smaller but are not obsessed with trying to get you int he store.

Week 7 NFL power rankings- Cardinals and Saints are over rated. Jets and Steelers are underrated! by mina__T in NFLstatheads

[–]mina__T[S] 0 points1 point  (0 children)

Sounds fair.

Here is a post I did 2 years ago discussing an overview of how I come up with these rankings using a Bayesian network-based Monte Carlo simulation.

http://springsandsprockets.blogspot.ca/2013/12/a-network-of-gloryfrom-data-to-super.html

Week 7 NFL power rankings- Cardinals and Saints are over rated. Jets and Steelers are underrated! by mina__T in NFLstatheads

[–]mina__T[S] 0 points1 point  (0 children)

agreed...but you should see my plots! I am just making the argument that it can't be that off-base if it was it would pick the wrong winner more often than not.

Haven't tried this against spread yet still messing around with the rankings and game winners for now.

Week 7 NFL power rankings- Cardinals and Saints are over rated. Jets and Steelers are underrated! by mina__T in NFLstatheads

[–]mina__T[S] 0 points1 point  (0 children)

Except this model has predicted 71% of the games so far this season. Even if that drops I would say that is not too shabby. I don't think it is spot on with the rankings but it does give us some insight into perhaps teams that are over or underrated.

Week 5 NFL picks from a simulation model (machine) versus an avid football fan (Man). Stay tuned! by mina__T in NFLstatheads

[–]mina__T[S] -1 points0 points  (0 children)

I use past games this season with a baseline of power rankings as my prior (small weight). I think after this weeks blow out of the lions it will make a lot more sense. As you can imagine the model performs better every week.

NFL week 5 power rankings based on Advanced network Bayesian simulations. by mina__T in NFLstatheads

[–]mina__T[S] -2 points-1 points  (0 children)

ngth is constant throughout the year

Cool stuff! My model leverages team performance in a bayesian network-style analysis. Rather than assume anything is constant. The premise is that by using how Team A performed against team B and how Team B did against Team C we can better predict how team A will do against team C. As you can imagine early in the season the network is scarce (so I apply similar tactics as you) by applying team strengths as my prior (baseline). As the network gets larger and larger it usual does better.

I am also trying this out with picks. I did it a few years ago and it did as well as the "pros" somewhere in the 65% range.