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On Demand

AMIA 10x10 with Oregon Health & Science University

Type:
AMIA 10x10
Course Level:
Introductory
Credits:
46.50
CME
Domains:
Clinical Informatics
Registration Deadline:
The Department of Medical Informatics & Clinical Epidemiology (DMICE) at Oregon Health & Science University will be offering another Biomedical Informatics Distance Learning Course as part of the AMIA 10x10 Program. The goal of this course is to provide a detailed overview of biomedical and health informatics to those who [...]
On Demand

JAMIA Journal Club Webinar - December 2021

Type:
Webinar
Predicting next-day discharge via electronic health record access logs Author You Chen, PhD, FAMIA discusses this month's JAMIA Journal Club selection: Zhang X, Yan C, Malin BA, Patel MB, Chen Y. Predicting next-day discharge via electronic health record access logs [published online ahead of print, 2021 Sep 30]. J Am [...]
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On Demand

AMIA 2022 Artificial Intelligence Evaluation Showcase Informational Webinar

Type:
Webinar
Artificial Intelligence is moving and shaping health and healthcare at lighting speed. The benefits of AI are multifold, but informatics research and practice is needed for the systematic and comprehensive evaluation of AI tools. AI in health and healthcare must be safely and effectively deployed in healthcare settings. Such evaluation [...]
On Demand

JAMIA Journal Club Webinar - October 2021

Type:
Webinar
A likelihood-based convolution approach to estimate major health events in longitudinal health records data: an external validation study Author Lisiane Pruinelli, PhD, MS, RN, FAMIA, discusses this month's JAMIA Journal Club selection: Pruinelli L, Zhou J, Stai B, et al. A likelihood-based convolution approach to estimate major health events in [...]
On Demand

JAMIA Journal Club Webinar - September 2021

Type:
Webinar
Credits:
1.00
CME
Identifying risk of opioid use disorder for patients taking opioid medications with deep learning Author Fusheng Wang, PhD, discusses this month's JAMIA Journal Club selection: Dong X, Deng J, Rashidian S, et al. Identifying risk of opioid use disorder for patients taking opioid medications with deep learning. J Am Med [...]