The only way I see to develop effective medical treatments and care models for many of the thousands of rare diseases is to pool the RESEARCH resources that individual countries are spending and the data countries are collecting about individual rare diseases and put those research resources under international control for prioritizing research agenda and ensuring public access to ALL results and research data.
Yes, I know the USA (probably the largest resource contributor) Congress will go in front of the television cameras and say that the failure of the United Nations and the disproportionate contributions to a pooled resource fund will ensure failure. They will point to the failure of the world to effectively coordinate collaborative research on HIV/AIDS and point to politics, homophobia, disrespect, and the hatred of American politics by certain national and fundamentalist groups and say we would be wasting our money by letting Africans and Arabs and the Russians and Chinese and Indians and Asians and South Americans collaborate with the USA on research and ensuring that research leads to effective treatments for at least some rare diseases.
Enough already. Let’s rise to the occasion of solving resource limitations in studying rare diseases and get an effective mechanism in place for expanding the impact of admittedly small research efforts by individual countries through international cooperation. I trust the governments of the world to collaborate, contribute as they can, and help us start to get some of these diseases treatable. Disease knows no boundaries.
In the last century we collectively developed very advanced medical research techniques. In this century we need to use these methods to solve all of the medical problems possible by putting aside the nonsense politics and nationalism and individual egos and predatory profits and focus on solving many medical issues and ensuring access to effective treatment world wide.
Here’s a way to start. Any yes, this is a test of our humanity and commitment to universal human rights of which medical treatment is but one. But let’s start somewhere that should be relatively easy to agree on (and let a few hundred angry politicians in the USA know that the world considers them bratty children and cannot tolerate their obstructionist and oppositional behavior).
Click on the image to expand. And let’s start the process of collaboration.
Can Big Data/Data Science avoid the train wreck of Big Pharma? I believe that the Big Data disaster will make the Big Pharma issues seem small in comparison.
But the issues will be about the same. A lot of the Big Pharma execs have become quite skilled at “beating the system” using “undocumented science” and many will move to Big Data and employ all of their very “best” moves and tricks. Big Data/Data Science has the potential to hurt the average individual even more than the greediness of Big Pharma.
HubaMap™ by g j huba phd
This afternoon I went to the local Panera and paid by credit card. My bank declined my charge of $4.82. I figured it was the magnetic strip on the card which had failed or that the new trainee using the cash register may have made a mistake. She ran the card three more times and it was rejected. Then I got four text messages from the bank saying that they are rejected my charges. To text me, they used my phone number.
I called. They had put a hold on my card because they had some questions about my charges from the prior few days. The red flag event was that I had made an earlier charge of $9.65 at Panera about eight hours before. Their computer program was not smart enough to figure out that it was not unreasonable for someone to have breakfast at 6:30am at a Panera in Durham and then walk into a Panera in Chapel Hill later in the day with 30 minutes to kill and had a coffee (and a Danish I probably should not have had) while I played with my iPad on their free wireless connection. The computer also questioned the $1 charge at a gas station this afternoon (which the human representative immediately recognized as the established practice of gas stations opening charge lines with their automated payment systems of $1 when you swipe your card and then next day putting a $92 charge on the card for filling the tank). I was also asked if the payment made on the account was one I had made (I asked the customer service rep if she thought that if someone had paid a bill for me that I would tell her it was an erroneous transaction and she laughed for a long time) as well as a $71 charge to a software company outside the US.
They had freaked out because they could not reach me by phone at three numbers that were old ones not active (I know they have my current number because they sent me texts at it and same bank sometimes calls about my other accounts at the cell phone I never turn off and which has a voice mailbox). Of course, if they did not have a no reply text address, I could have responded to the four texts they sent.
Predictive models have been around for a decade or more in banks as they attempt to identify fraud and protect themselves. The episodes I have with my bank about every 2-3 months illustrate what happens when somebody blindly runs predictive analytic programs through big datasets without using some commonsense to guide the modeling process. Just because anyone can buy a $100,000 program from IBM or others for developing predictive analytics does not mean that the model that comes out of the Big Data and expensive program makes any sense at all.
Or that the NSA or FBI or CIA or Google or Amazon models make much sense as they probe your private information.
If a computer predictive system is going to think that somebody is committing credit card fraud because they purchase two cups of coffee at the same national restaurant chain in a day, we are in big trouble.
The bottom line is that Big Data models are going to have to be regulated before some idiot accidentally turns on Sky Net.
Or maybe the problem is that the NSA or FBI or CIA or Google has done it already.
There have been several new “blank canvas” Mac apps released recently. The main three are Scapple (A+), Delineato Pro (A-) and Mindix (still in early development). These programs are not mind mapping ones. They are very simple ways of cutting and pasting snippets, links, pictures, paragraphs and other information onto a large canvas or sheet of paper like those we used to decorate the walls during meetings.
The mind map below shows features of the various blank canvas apps.
Scapple and Delineato are both highly recommended.
ADDITION March 2, 2014: Big Hairy Goal has recently been released for the Mac and is comparable to Mindix but much more highly developed. I consider Big Hairy Goal worth rating A.
Between 2008 and 2010 (when I discovered Twitter), I published a blog. Here is one of my favorite posts from that time. It still applies today as much as back then.
Please click on the text below to zoom in.
Irv Oii is known to many international news organizations and researchers as a star data journalist. Being a home worker (although home may be the UK, Ohio, the Middle East, Central Africa, Hong Kong, or Antartica) and a fairly reclusive person, nobody seems to have met Irv. Some speculate that he might be a Jewish Asian-American. Others believe Irv is short for Irvelina, a Russian immigrant physician who went to Ohio (or was it Ojai, California) when the Soviet science programs collapsed and turned into the lower funded Russian collaborative efforts with the EU and USA. The collapse of the Soviet Union resulted in the closing of her laboratory in Minsk. Some even think Irv Oii is an acronym.
Irv is thus an enigma and no pictures of her/him seem to exist. An artist’s conception (mine) based on the writings and consultations of Irv Oii on healthcare breakthroughs is shown below. My belief is that a portrait of Irv should hang over the desk of every data journalist and researcher.
Please click the image to zoom.