Collaboration Phenotypes

Contact authors listed below are open to engaging others in the development of their phenotypes. Unless the status of the phenotype is marked as final, these phenotypes cannot be viewed in-depth until the author has shared access with you and you have logged into PheKB. Click on an author's name to send an email to him or her expressing your interest in collaborating.

Title Institution Phenotype Attributes Description Status Contact Author Type of Phenotype
STOP CRC Cohort Group Health Cooperative CPT Codes, ICD 9 Codes This is a cohort identification phenotype for the STOP CRC trial, which is testing a culturally tailored, health care system–based program to improve CRC screening rates in OCHIN, a community-based collaborative network of more than 200 Federally Qualified Healthcare Centers. Validated Michelle Smerek Disease or Syndrome
Systemic lupus erythematosus (SLE) Vanderbilt University Medical Center ICD 9 Codes, Laboratories, Medications, Natural Language Processing We used Vanderbilt’s Synthetic Derivative (SD), a de-identified version of the EHR, with 2.5 million subjects. We selected all individuals with at least one SLE ICD-9 code (710.0) yielding 5959 individuals. To create a training set, 200 were randomly selected for chart review. A subject was defined as a case if diagnosed with SLE by a rheumatologist, nephrologist, or dermatologist. Final April Barnado Disease or Syndrome
Tourette Syndrome Vanderbilt University Medical Center ICD 10 Codes, ICD 9 Codes, Natural Language Processing Testing Lea Davis Disease or Syndrome
Type1 or Type 2 Diabetes Mellitus Mayo Clinic ICD 9 Codes, Laboratories, Medications, Natural Language Processing 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. Final Sudhi Upadhyaya
Urinary Incontinence Stanford University CPT Codes, ICD 10 Codes, ICD 9 Codes, Natural Language Processing 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 Tina Hernandez-Boussard Disease or Syndrome