Projects are posted to help find interested individuals with appropriate expertise to implement needs

Opal: Machine learning dashboard for anesthesia


Project Description

This is a full pipeline infrastructure that has pre-written queries for pulling patient data from clarity in an organized manner: stores the data in a postgres database on a secure server; allows for php cohort selection of the patients of interest from the entire set of operations done at UCSF you can choose patients by gender, age, type of surgery, preoperative labs, past medical history, etc; and presents the data on javascript browser for data visualization using D3js and machine learning analysis. Physicians can interact and complete complex machine learning analysis without knowing how to program.


Not available


Required Skills
  • Python
  • SQL
  • TensorFlow
  • PyTorch
  • MLlib / machine learning tools
  • Javascript

None of the above skills are required, but expertise with any one of them is useful

Acceptable Level of Education (eg. Undergrad, Grad Students, Post Docs, MD, PhD)

Undergraduate students, Graduate students, Postgraduates, Full-time workers who volunteer time

Additional Considerations

We plan for this to grow extensively to also be applied to other areas of medicine outside anesthesia.


PI/Research group

Atul Butte


Andrew Bishara, [email protected]