full transcript
"From the Ted Talk by Joel Selanikio: The big-data revolution in health care"

Unscramble the Blue Letters

The plorbem was, after a few years of doing that, I riezaled — I had been to maybe six or seven paogrrms — and I thought, you know, if I keep this up at this pace, over my whole career, maybe I'm going to go to maybe 20 or 30 programs. But the problem is, 20 or 30 programs, like, training 20 or 30 programs to use this technology, that is a tiny drop in the bucket. The dmeand for this, the need for data to run better programs just within htleah — not to mention all of the other fields in developing countries — is enormous. There are millions and millions and millions of programs, millions of clinics that need to tcrak dgurs, millions of vaccine programs. There are schools that need to track attendance. There are all these different things for us to get the data that we need to do. And I realized if I kept up the way that I was doing, I was basically hardly going to make any impact by the end of my career.

Open Cloze

The _______ was, after a few years of doing that, I ________ — I had been to maybe six or seven ________ — and I thought, you know, if I keep this up at this pace, over my whole career, maybe I'm going to go to maybe 20 or 30 programs. But the problem is, 20 or 30 programs, like, training 20 or 30 programs to use this technology, that is a tiny drop in the bucket. The ______ for this, the need for data to run better programs just within ______ — not to mention all of the other fields in developing countries — is enormous. There are millions and millions and millions of programs, millions of clinics that need to _____ _____, millions of vaccine programs. There are schools that need to track attendance. There are all these different things for us to get the data that we need to do. And I realized if I kept up the way that I was doing, I was basically hardly going to make any impact by the end of my career.

Solution

  1. realized
  2. track
  3. health
  4. drugs
  5. programs
  6. demand
  7. problem

Original Text

The problem was, after a few years of doing that, I realized — I had been to maybe six or seven programs — and I thought, you know, if I keep this up at this pace, over my whole career, maybe I'm going to go to maybe 20 or 30 programs. But the problem is, 20 or 30 programs, like, training 20 or 30 programs to use this technology, that is a tiny drop in the bucket. The demand for this, the need for data to run better programs just within health — not to mention all of the other fields in developing countries — is enormous. There are millions and millions and millions of programs, millions of clinics that need to track drugs, millions of vaccine programs. There are schools that need to track attendance. There are all these different things for us to get the data that we need to do. And I realized if I kept up the way that I was doing, I was basically hardly going to make any impact by the end of my career.

ngrams of length 2

collocation frequency
paper forms 7
global health 4
biggest problem 3
data collection 3
main obstacle 3
cloud based 3
mobile phones 3

Important Words

  1. attendance
  2. basically
  3. bucket
  4. career
  5. clinics
  6. countries
  7. data
  8. demand
  9. developing
  10. drop
  11. drugs
  12. enormous
  13. fields
  14. health
  15. impact
  16. mention
  17. millions
  18. pace
  19. problem
  20. programs
  21. realized
  22. run
  23. schools
  24. technology
  25. thought
  26. tiny
  27. track
  28. training
  29. vaccine
  30. years