Print Jobs just got easier- especially if you prefer one printer, use Google Chrome, and can take 2 minutes to set up your printer to print from anywhere in the world through the internet.
It’s called Google Cloud Print– and it makes my life a lot easier when I travel and need to give to printer at home some documents to print rather than rely on external printers. See screenshots below and check out http://www.google.com/cloudprint/ for more
More than 71 Million individuals in the United States are admitted to
hospitals each year, according to the latest survey from the American
Hospital Association. Studies have concluded that in 2006 well over
$30 billion was spent on unnecessary hospital admissions. Each of
these unnecessary admissions took away one hospital bed from someone
else who needed it more.
The goal of the prize is to develop a predictive algorithm that can identify patients who will be admitted to the hospital within the next year, using historical claims data.
Official registration will open in 2011, after the launch of the prize. At that time, pre-registered teams will be notified to officially register for the competition. Teams must consent to be bound by final competition rules.
Registered teams will develop and test their algorithms. The winning algorithm will be able to predict patients at risk for an unplanned hospital admission with a high rate of accuracy. The first team to reach the accuracy threshold will have their algorithms confirmed by a judging panel. If confirmed, a winner will be declared.
The competition is expected to run for approximately two years. Registration will be open throughout the competition.
Data Sets
Registered teams will be granted access to two separate datasets of de-identified patient claims data for developing and testing algorithms: a training dataset and a quiz/test dataset. The datasets will be comprised of de-identified patient data. The datasets will include:
Outpatient encounter data
Hospitalization encounter data
Medication dispensing claims data, including medications
Outpatient laboratory data, including test outcome values
The data for each de-identified patient will be organized into two sections: “Historical Data” and “Admission Data.” Historical Data will represent three years of past claims data. This section of the dataset will be used to predict if that patient is going to be admitted during the Admission Data period. Admission Data represents previous claims data and will contain whether or not a hospital admission occurred for that patient; it will be a binary flag.
The training dataset includes several thousand anonymized patients and will be made available, securely and in full, to any registered team for the purpose of developing effective screening algorithms.
The quiz/test dataset is a smaller set of anonymized patients. Teams will only receive the Historical Data section of these datasets and the two datasets will be mixed together so that teams will not be aware of which de-identified patients are in which set. Teams will make predictions based on these data sets and submit their predictions to HPN through the official Heritage Health Prize web site. HPN will use the Quiz Dataset for the initial assessment of the Team’s algorithms. HPN will evaluate and report back scores to the teams through the prize website’s leader board.
Scores from the final Test Dataset will not be made available to teams until the accuracy thresholds are passed. The test dataset will be used in the final judging and results will be kept hidden. These scores are used to preserve the integrity of scoring and to help validate the predictive algorithms.
Teams can begin developing and testing their algorithms as soon as they are registered and ready. Teams will log onto the official Heritage Health Prize website and submit their predictions online. Comparisons will be run automatically and team accuracy scores will be posted on the leader board. This score will be only on a portion of the predictions submitted (the Quiz Dataset), the additional results will be kept back (the Test Dataset).
Once a team successfully scores above the accuracy thresholds on the online testing (quiz dataset), final judging will occur. There will be three parts to this judging. First, the judges will confirm that the potential winning team’s algorithm accurately predicts patient admissions in the Test Dataset (again, above the thresholds for accuracy).
Next, the judging panel will confirm that the algorithm does not identify patients and use external data sources to derive its predictions. Lastly, the panel will confirm that the team’s algorithm is authentic and derives its predictive power from the datasets, not from hand-coding results to improve scores. If the algorithm meets these three criteria, it will be declared the winner.
Failure to meet any one of these three parts will disqualify the team and the contest will continue. The judges reserve the right to award second and third place prizes if deemed applicable.
Julian Assange a very Dear Chap
couldnt control his pecker
got caught in a honey trap
Should have kept that rubber on, Jules
Nordic Scandinavians may be easy but even they have rules
meanwhile Dear Chap’s Website the eponymous Wikileaks
is leaking revolution and democracy like Vegas casino magic tricks
The Arabs read his website before Sentor Joe crashed it down
And now Anglo Saxon allies in Egypy, Tunisia, Libya, Yemen, Bahrain are wearing a frown
Viva La Website Revolution Wikileaks
Merde to the Dear Chap\s pecker squeaks
Time up, time for all dictators to go and hide,
rulers Arabian, or Aussi hackers on a funny ride.
I met a traveller from an antique land
Who said: Two vast and trunkless legs of stone
Stand in the desert. Near them, on the sand,
Half sunk, a shattered visage lies, whose frown
And wrinkled lip, and sneer of cold command
Tell that its sculptor well those passions read
Which yet survive, stamped on these lifeless things,
The hand that mocked them and the heart that fed.
And on the pedestal these words appear:
“My name is Ozymandias, king of kings:
Look on my works, ye Mighty, and despair!”
Nothing beside remains. Round the decay
Of that colossal wreck, boundless and bare
The lone and level sands stretch far away.[1]
In Egypt’s sandy silence, all alone,
Stands a gigantic Leg, which far off throws
The only shadow that the Desert knows:
“I am great OZYMANDIAS,” saith the stone,
“The King of Kings; this mighty City shows
“The wonders of my hand.” The City’s gone,
Nought but the Leg remaining to disclose
The site of this forgotten Babylon.
We wonder, and some Hunter may express
Wonder like ours, when thro’ the wilderness
Where London stood, holding the Wolf in chace,
He meets some fragments huge, and stops to guess
What powerful but unrecorded race
Once dwelt in that annihilated place.
Here is a brief dataset I out after one hour of cutting and pasting from WordPress.com’s creative data style formats. It shows spam,comments,traffic, and number of posts written monthly.
Clearly monthly traffic is directly related to number I write (suppose A + B* Posts)
But Spam is showing a discontinuous growth especially after a big month (in which Reddit helped)
Akismet had some missing historical values (which is curious)
At the user’s choice, statistical output and graphics are done in ASCII, PDF, PostScript or HTML formats. A limited range of statistical graphs can be produced, such as histograms, pie-charts and np-charts.
At the user’s choice, statistical output and graphics are done in ASCII, PDF, PostScript or HTML formats. A limited range of statistical graphs can be produced, such as histograms, pie-charts and np-charts.
The training dataset includes several thousand anonymized patients and will be made available, securely and in full, to any registered team for the purpose of developing effective screening algorithms.
DECISION STATS 