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--- documentation:software:atlas:prediction [2017/10/17 13:49]
jhardin created
+++ documentation:software:atlas:prediction [2019/05/30 20:46] (current)
anthonysena
@@ Line 1: / Line 1: @@
-This page will describe the use of the Prediction feature in ATLAS.
+===== IMPORTANT NOTE =====
+All ATLAS documentation has moved to [[https://github.com/OHDSI/ATLAS/wiki|GitHub]]. Please disregard the content below as it is legacy and kept for posterity.
+===== Prediction (LEGACY) =====
+ATLAS has embedded the ability to generate prediction models using machine learning methods for precision medicine and disease interception, including:
+  * Regularized regression
+  * Random forest
+  * k-nearest neighbors
+The ATLAS prediction feature uses the R package PatientLevelPrediction that builds patient level predictive models using data in Common Data Model format.
+Features:
+  * Takes a cohort and outcome of interest as input.
+  * Extracts the necessary data from a database in OMOP Common Data Model format.
+  * Uses a large set of covariates including for example all drugs, diagnoses, procedures, as well as age, comorbidity indexes, etc.
+  * Large scale regularized regression to fit the predictive models.
+  * Includes function for evaluating predictive models.
+  * Supported outcome models are logistic, Poisson, and survival (time to event).
+This feature can be accessed by clicking on the Prediction menu item; there are options for inputs in the ATLAS prediction page.
+{{:documentation:software:atlas:atlas_plp_details.png?800|}}
+Additional details can be found by viewing a video tutorial: https://youtu.be/BEukCbT8UoA. And/or review of the github repository: https://github.com/OHDSI/PatientLevelPrediction

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