This is the HealthCare Twitter Analysis Open Source Project. Project started via Coursera course by Pratik Mehta and Joon Lee on May 10th 2013. Thanking, coursera course 'Introduction to Data Science' taught by Bill Howe.
We strongly believe that Medical Care Quality can be improved using Data Science. The challenge is to detect medical comments & events, create models, generate insights, and finally correlate it to Medical Care to suggest improvements in the quality of care.
We are going to tackle some of these problems and try to seek insights into the US Medical Care System using Social Media (Twitter). We would love to collaborate with the community of data scientists to solve this problem together.
Project Milestones 0) Download live tweets and classify every Tweet as Medical or Non - Medical.
-
Find what people are happy and not happy about. (Clustering / Sentiment)a) Find key topics that the tweets talk about. (clustering all tweet and finding related topics)b) Find sentiment around those topics (polarity and emotion)(Example Find : A large bunch of tweets are talking about high payments and people are unhappy about it.)
-
Detect Trending Medical Topics. Extension : Detect Disease Patterns (Trends) by Geography
-
(Advanced) Recommender System - Find Specific problems and suggest improvements in the medical industry.
Any analysis or creative thoughts are welcome.
Please email me (Pratik Mehta) at [email protected] with any queries.