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documentation:software:atlas:prediction [2017/10/17 15:12] jhardin |
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+ | ===== 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: | ATLAS has embedded the ability to generate prediction models using machine learning methods for precision medicine and disease interception, including: | ||
- | Regularized regression | + | * Regularized regression |
- | Random forest | + | * Random forest |
- | k-nearest neighbors | + | * k-nearest neighbors |
- | This feature can be accessed by clicking on the Prediction menu item. ATLAS prediction feature uses the R package called PatientLevelPrediction that builds patient level predictive models using data in Common Data Model format. | + | The ATLAS prediction feature uses the R package PatientLevelPrediction that builds patient level predictive models using data in Common Data Model format. |
Features: | Features: | ||
- | Takes a cohort and outcome of interest as input. | + | * Takes a cohort and outcome of interest as input. |
- | Extracts the necessary data from a database in OMOP Common Data Model format. | + | * 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. | + | * 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. | + | * Large scale regularized regression to fit the predictive models. |
- | Includes function for evaluating predictive models. | + | * Includes function for evaluating predictive models. |
- | Supported outcome models are logistic, Poisson, and survival (time to event). | + | * Supported outcome models are logistic, Poisson, and survival (time to event). |
- | A video tutorial is available: https://github.com/OHDSI/PatientLevelPrediction. | + | 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 | ||