That’s a lot of data. It takes machines and algorithm to process. Intelligence of the artificial type. Automated processing.
So who manages the machines? Who decides what patterns to watch for? What can be learned from it.
Big data is a term that has become increasingly tossed around at research meetings and medical conferences. The multi-centre RCT is under attack. It’s expensive, restrictive and only ever seems to beget more RCTs. Is Big Data here to replace RCTs or to refine it?
Big data may be more reflective of real world practice and variance. Like a mega-collection of annecdotal evidence – a Megadote, or maybe a Metadote.
Nik Kumar is an ICU registrar who trundled along to the ANZICS Datathon in April to see what all the fuss was about and whether he could use it for some of the projects he had in mind. He went with few expectations. He came back with a whole new perspective on not just data collection and analysis but on collaborative research and future directions for determining trends in practice. He also likes pizza.
Big thanks to Matt for recording another Jellybean. Thanks to Dr Nik Kumar for explaining some high end health focused data science. It is not a main stream thing. (Yet.) It is one of those interesting things that hang around at the edges of our working lives.
Here at the Jellybean podcast, we love the fringes. We love to learn a little more about the stuff that isn’t in the books, that’s not on any syllabus but is relevant. It might seem small but as we should all know; from little things big things grow.
Thanks to Big Data for making the music. We couldn’t resist using one of their tunes. The intro and outro music is from Big Data’s track Dangerous
You kind find more info on this big Big Data thing here;
Big data analysis – The Basics
Machine learning – The Basics
– Machine Learning in Medicine. Rahul C. Deo. Circulation. 2015 Nov 17; 132(20): 1920ñ1930. Circulation. 2015 Nov 17; 132(20): 1920ñ1930. (Full text)