The science of informatics and predictive analytics
Year: 2019
Type: editorial
Abstract: As an interdisciplinary technologically driven field, the science of informatics is rapidly evolving. In this issue of Journal of the American Medical Informatics Association, we bring together a series of articles and commentaries that describe various aspects of the science of predictive modeling. These articles describe work to ensure that models are useful and valid on release and, perhaps more importantly, continue to be so as clinical processes and patient populations evolve over time. The upshot of the collection is to point out a new direction for informatics research and policy advocacy in the development of models for predictive analytics. Rather than focus on the mechanics of model building and validation, scientists should now be focused on how to document the model,1 when it is likely to yield benefits,2 what the model life cycle is,3 how to maintain models in a sustainable way,4 and even which types of health care offer the optimal predictive performance.5
DOI: 10.1093/jamia/ocz202
Author: Leslie Lenert
Institution: Medical University of South Carolina
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W2985591740