Shah Lab

User Tools

Site Tools

You are here: start » biomedin215
biomedin215

Differences

This shows you the differences between two versions of the page.

Link to this comparison view

Both sides previous revision Previous revision
Next revision 		Previous revision
biomedin215 [2020/09/04 11:52]
nigam 		biomedin215 [2023/09/01 14:42] (current)
nigam
Line 1: Line 1:
-====== BIOMEDIN 215: Data Science for Medicine (Aut 2020) ======+====== BIOMEDIN 215: Data Science for Medicine (Aut 2023) ======
  
-In the Autumn quarter of 2020, this class will be offered online. In the past years, the [[:biomedin215_precovid|pre-COVID]] offering was a highly interactive, in person experience. We wish to preserve as much of the learning experience as possible in a virtual setting. Therefore, to ease the transition of converting the class content for offering on Zoom, enrollment in 2020 will be limited to graduate students in the Biomedical Informatics (BMI) Program.+The Autumn 2023 class will be offered in person.
  
-I have chosen to do this so that we can maintain an effective learning experience for those students for whom this is a required class. If you are not a BMI student, thank you for understanding. I look forward to meeting you in the regular offering of the class next Autumn. +– 2023 Teaching team: Nigam Shah, Alison Callahan, Bryan Bunning, Maggie Wang, Ben Viggiano, Yixing Jiang
- +
-– 2020 Teaching team: Nigam Shah, Alison Callahan, Conor Corbin, Minh Nguyen, Erin Craig+
  
 This course is designed to prepare you to pose and answer meaningful clinical questions using routinely collected healthcare data. The practical skills you will learn in this class will be applicable to any task involving data manipulation and analysis. The course will use real, de-identified, large size patient datasets for home work projects associated with the course. To have the best learning experience, you will need to be proficient in the R language. This course is designed to prepare you to pose and answer meaningful clinical questions using routinely collected healthcare data. The practical skills you will learn in this class will be applicable to any task involving data manipulation and analysis. The course will use real, de-identified, large size patient datasets for home work projects associated with the course. To have the best learning experience, you will need to be proficient in the R language.
Line 17: Line 15:
   - apply your knowledge to evaluate and criticize published clinical informatics research.   - apply your knowledge to evaluate and criticize published clinical informatics research.
  
-The syllabus for 2020 is [[https://docs.google.com/document/d/1xGrq046B09O8g8xkbzcTlos07ZjkdvCDuxtn-oeqzOQ/edit?usp=sharing|here]] \\ 
-Schedule: TUE, THU 2:30 PM - 3:50 PM on Zoom 
  
-<html> <iframe width='900' height='580' frameborder='0'src="https://docs.google.com/spreadsheets/d/e/2PACX-1vQb9V9BNOzmP7fd1442lelh8oXcIhRZKibGzNboT-jLirbJOSi3aNFzeLu_CFq3zmMs4S1mv6kPSvp2/pubhtml?gid=34616104&single=true&widget=true&headers=false"></iframe> </html>+Schedule: TUE, THU 1:30 PM - 2:50 PM in Gates B3. \\ 
 +For Office Hours, see the [[https://canvas.stanford.edu/courses/178048 | Canvas site]] (log in with your SUNet id) \\ 
 +Pre-requisites: See the [[https://docs.google.com/document/d/1se4LuFfeIpZBzgiGL5AM57jg_dBOCG37nNWdIfEoYZQ/edit|syllabus]] 
 + 
 +<html> 
 + 
 +<iframe width='900' height='580' frameborder='0's src="https://docs.google.com/spreadsheets/d/e/2PACX-1vSUt9Hf34dkX_ioxJugITzOo_HhqbRC2kXTEW6auFRvAsxQzxxmRFPI3Ued8SuFGCIHuBWRwxGz7EGL/pubhtml?gid=34616104&single=true&widget=true&headers=false"></iframe></html> //
  
  
biomedin215.1599245574.txt.gz · Last modified: 2020/09/04 11:52 by nigam

Page Tools

Donate Powered by PHP Valid HTML5 Valid CSS Driven by DokuWiki