November 17, 2024
Learn practical applications of common machine learning concepts and techniques for healthcare and pharmaceutical outcomes research!
Healthcare data are often available to payers and healthcare systems in real time but are massive, high dimensional, and complex. Artificial intelligence and machine learning merge statistics, computer science, and information theory and offer powerful computational tools to enhance the extraction of useful information from complex healthcare data and prediction accuracy.
Enroll in this course to:
- Understand foundational principles and concepts of statistical machine learning.
- Explore several specific machine learning techniques and their applications in health and pharmaceutical outcomes research.
- Explore how R or Radiant can be used for several machine learning methods, such as penalized regression and tree-based methods, as well as techniques for dimension reduction/feature selection.
- Engage in hands-on, practical experiences with machine learning.
- Gain experience interpreting and evaluating the results and prediction performance that comes from machine learning modeling.
- Discuss and distinguish prediction modeling from causal inference research in pharmacoepidemiology.
This short course is offered in-person at the ISPOR Europe 2024 conference.
*Conference attendance is not required to attend an ISPOR Short Course. Separate registration is required for conference attendees.
LEVEL: Intermediate
TRACK: Methodological & Statistical Research
HEOR Key Competency (2024): 10.3 Artificial Intelligence (AI) and Machine Learning (ML)
LENGTH: 4 Hours | Course runs 1 day
FACULTY MEMBERS
Schedule:
Sunday, 17 November 2024 | Course runs 1 Day
13:00-17:00 Central European Time (CET)
Register Here
*Conference attendance is not required to attend an ISPOR Short Course. Separate registration is required for conference attendees.
Visit the ISPOR Europe 2024 Program page to view all short courses offered.