Type 1 Diabetes
Phenotype Algorithm for Type 1 Diabetes – eMERGE Phase-IV Program
Owner Phenotyping Groups:
Final
Other Race
Type 2 Diabetes (T2D)
There are two case algorithms provided for T2D. The first (t2d_dprism_ehr_plus_1) is the preferred case algorithm and includes self-reported T2D information collected from survey. The second (t2d_dprism_ehr_1) is an alternative case algorithm that does NOT include self-reported T2D information collected from survey.
We request harmonization based on the preferred algorithm, but if self-reported T2D survey information is not available, the alternative algorithm is acceptable.
Owner Phenotyping Groups:
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Final
Type1 or Type 2 Diabetes Mellitus
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.
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Final
Urinary Incontinence
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.
Final
Venous Thromboembolism (VTE)
Recently published GWAS of VTE done by Mayo: http://www.ncbi.nlm.nih.gov/pubmed/22672568
Owner Phenotyping Groups:
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Final