Type 2 Diabetes - Demonstration Project
Type 2 Diabetes phenotype algorithm for the DNA Databank Demonstration Project.
Type 2 Diabetes phenotype algorithm for the DNA Databank Demonstration Project.
NOTE:
The following files were updated on 4/9/2021 so that the output of the #feature table in the eMERGE_IV_OMOP_T2DM_PRS_algorithm script matches the data dictionary.
Files:
Phenotyping algorithm for the identification of patients with type 1 or type 2 diabetes mellitus (DM) preoperatively using routinely available clinical data from electronic
health records.
Description of a weakly supervised machine learning approach for extracting treatment-related side effects (Urinary Incontinence) following prostate cancer therapy from multiple types of free-text clinical narratives, including progress notes, discharge summaries, history and physical notes. Prostatectomy surgery and radiation therapy are our treatments of interest for prostate cancer.
Recently published GWAS of VTE done by Mayo: http://www.ncbi.nlm.nih.gov/pubmed/22672568
This algorithm identifies patients who have a stable within-range INR (assuming a target INR of 2-3) over at least a three week period and correlates with their warfarin weekly dose. It is used to identify pharmacogenetics behind warfarin stable dose.
Genetic variation that predicts white blood count (WBC) and it differential, a marker of the health of the immune system.
WBC is unique among the identified inflammatory predictors of chronic disease in that it has been routinely measured in healthy patients in an unbiased way for the duration of the electronic medical record data.