In OHDSI/PatientLevelPrediction: Develop Clinical Prediction Models Using the Common Data Model

Clinical models developed using the OHDSI PatientLevelPrediction framework

| Title | Link | |----------------------|-------| | Using Machine Learning Applied to Real-World Healthcare Data for Predictive Analytics: An Applied Example in Bariatric Surgery | Value in Health |
| Development and validation of a prognostic model predicting symptomatic hemorrhagic transformation in acute ischemic stroke at scale in the OHDSI network | PLoS One |
| Wisdom of the CROUD: development and validation of a patient-level prediction model for opioid use disorder using population-level claims data | PLoS One | | Developing predictive models to determine Patients in End-of-life Care in Administrative datasets | Drug Safety |
| Predictors of diagnostic transition from major depressive disorder to bipolar disorder: a retrospective observational network study | Translational psychiatry |
| Seek COVER: using a disease proxy to rapidly develop and validate a personalized risk calculator for COVID-19 outcomes in an international network | BMC Medical Research Methodology |
| 90-Day all-cause mortality can be predicted following a total knee replacement: an international, network study to develop and validate a prediction model | Knee Surgery, Sports Traumatology, Arthroscopy |
| Machine learning and real-world data to predict lung cancer risk in routine care | Cancer Epidemiology, Biomarkers & Prevention |
| Development and validation of a patient-level model to predict dementia across a network of observational databases | BMC medicine |

OHDSI/PatientLevelPrediction documentation built on Feb. 14, 2025, 9:44 a.m.