Category: Data Modeling & Design
Brand: O'Reilly Media
Item Page Download URL : Download in PDF File
Rating : 4.2
Buyer Review : 12
Description : This particular How Data Science Is Transforming Health Care does great, simple to operate and also alter. The price for is was reduced than other places My partner and i researches, and not considerably more when compared with similar merchendise
This kind of item Offer surpass own prospect, that one has become a great buy for personally, The thought arrived properly and also swiftly How Data Science Is Transforming Health Care
In the early days of the 20th century, department store magnate John
Wanamaker famously said, "I know that half of my advertising doesn't
work. The problem is that I don't know which half." That remained
basically true until Google transformed advertising with AdSense based
on new uses of data and analysis. The same might be said about health
care and it's poised to go through a similar transformation as new
tools, techniques, and data sources come on line. Soon we'll make
policy and resource decisions based on much better understanding of
what leads to the best outcomes, and we'll make medical decisions
based on a patient's specific biology. The result will be better
health at less cost.
This paper explores how data analysis will help us structure the
business of health care more effectively around outcomes, and how it
will transform the practice of medicine by personalizing for each
specific patient.
Review :
How combining data and outcomes can change the way we practice health care...
How Data Science Is Transforming Health Care by Tim O'Reilly, Mike Loukides, Julie Steele, and Colin Hill is not a large book... in fact, it's only 26 pages. But it's a solid 26 pages that makes the case for how health care can (and will) be transformed by the use of massive and detailed data on patients and outcomes. Given that you can download it for free on Amazon, there's no reason *not* to give it a read. It's enough to shift your view of how health care technology can be much more effective than it currently is...
Probably the most significant point made is how the combination of data on patients and outcomes can be combined to make drug therapy more targeted and efficient. Instead of having a drug that is 80% effective in patients, we can move to having a drug that is 100% effective in 80% of the patients, and we know not to travel down that path for the other 20% where it will fail. Learning how drugs interact with certain gene makeups can narrow down the most...
Interesting but it barely scratches the surface
very nice read
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