7 Big Data Solutions Try To Reshape Healthcare - InformationWeek
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Paul Cerrato
Paul Cerrato
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7 Big Data Solutions Try To Reshape Healthcare

Big data medicine is still largely unproven, but that's not stopping several medical centers and analytics vendors from jumping in with both feet.
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During a recent Digital Health Conference sponsored by the New York eHealth Collaborative, Martin Kohn, M.D., chief medical scientist at IBM, and Pat Skarulis, CIO at Memorial Sloan-Kettering Cancer Center (MSKCC) in New York, outlined a joint venture to use the Watson supercomputer's big data capabilities to help oncologists provide better care for MSKCC patients.

Kohn pointed out that Watson isn't just a "search engine on steroids," or even a massive database. It relies on parallel probabilistic algorithms to analyze millions of pages of unstructured text in patient records and the medical literature to locate the most relevant answers to diagnostic and treatment-related questions.

Ninety percent of the world's data has been created in the last two years, and 80% of that data is unstructured. As any clinician with a pile of unread medical journals knows, that massive collection of information includes far too many papers for any one human to read.

Watson reads it for them at lightening fast speed.

With the help of natural language processing (NLP), the computer not only pulls out relevant terms to match the search terms in a clinician's query, but it also understands the idioms and other idiosyncratic expressions in the English language. And with the help of temporal, statistical paraphrasing and geospatial algorithms, it finds meaningful relationships between the clinician's question and its massive collection of medical facts and theories.

MSKCC decided to collaborate with IBM to "build an intelligence engine to provide specific diagnostic test and treatment recommendations," Skarulis said. The two organizations now are combining data from MSKCC's massive database, called Darwin, with all of Watson's NLP capabilities. IBM is using all of the medical center's structured patient data and its NLP tools to convert the medical center's free text consultation notes into usable data. Skarulis hopes to launch a pilot shortly that will allow the supercomputer to work on real medical cases.


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User Rank: Apprentice
6/20/2014 | 2:25:37 PM
Amazing Data Solution Company
This is definitely a unique somewhat new technoloy, however, it is very important that we learn how effective and accurate the information is. I have been reading about the technology and researching fo the past five months. One new company, I find to be intersting is Due North Analytics.

They are a start up but seem to have an advantage. They provide cutting edge analytics for healthcare institutions. They totally understand the importance of Big Data for the industry. They started their company knowing they could help Healthcare institutions do three things. 

1 Predict potential rates, so they can predict the fluctuation of symptoms and plan accordingly with staffing, equipment and insurance rates. 2. Predict patient trends so that they can understand what diseases the patients may be vulnerable to in the future. 3. Determine the effectiveness of medication. Knowing what is working and not working could save patients, hospitals, and insurance companies a lot of money. Check out their website I know you will be impressed with their capabilities.

User Rank: Apprentice
1/3/2013 | 3:50:55 PM
re: 7 Big Data Solutions Try To Reshape Healthcare
During my interviews with Big Data vendors and medical centers, I did see some tangible results, but in some cases they were improvements in "intermediate endpoints," as medical researchers like to phrase it.

Improvements in blood glucose or serum cholesterol levels in patients whose data has been crunched is worthwhile, but it's not the same as documented evidence that the analysis reduced cardiac deaths or limb amputations. Those are the real endpoints we need to reach.
Paul Cerrato
InformationWeek Healthcare
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