RESEARCH
Creating dynamic visualizations to investigate research questions and to foster student learning outcomes.
DSC
/
Research
Below are select projects from the DSC's research and work. If you are looking for a particular project's information and don't see it, please feel free to contact us via the Contact Page and we will be in touch!
Pulmonary Medicine Ventilator Transition EHR Inquiry
Department: CCHMC Pulmonary Medicine
Researcher: Nathan Pajor, MD
Dataset and Source: [Language and meta-data from Respiratory Therapist notes for CCHMC Pulmonary Medicine patients on respiratory ventilators during first year of life that have attempted transition to an at-home ventilator.
Status: In Progress
DSC Team Members: Lindsay Nickels, Ezra Edgerton, Sally Luken, Anubhav Maity Goals and/or Outcomes: Identify patterns, themes, or correlations in dataset that may indicate likelihood of patient transition outcomes, indicate needs for improved patient care, and/or provide insight into physician note-keeping behavior related to patient outcome. Methods and tools include WordSmith Tools corpus linguistic software, semi-supervised data analysis, the DSC Platform, and Python Jupyter Notebooks.
Researcher: Nathan Pajor, MD
Dataset and Source: [Language and meta-data from Respiratory Therapist notes for CCHMC Pulmonary Medicine patients on respiratory ventilators during first year of life that have attempted transition to an at-home ventilator.
Status: In Progress
DSC Team Members: Lindsay Nickels, Ezra Edgerton, Sally Luken, Anubhav Maity Goals and/or Outcomes: Identify patterns, themes, or correlations in dataset that may indicate likelihood of patient transition outcomes, indicate needs for improved patient care, and/or provide insight into physician note-keeping behavior related to patient outcome. Methods and tools include WordSmith Tools corpus linguistic software, semi-supervised data analysis, the DSC Platform, and Python Jupyter Notebooks.
Tags :
- Electronic Health Record Machine Learning Classification