Hematology/Oncology 2019 Projects

Project Title: Evaluation of baseline quality improvement and patient safety in interns

Faculty Mentor’s Name: Dr. Julia Close
Email: jclose@ufl.edu

Student’s Name: Andrew Dobry
Email: andrew.dobry@ufl.edu

Project Description:

Study includes collection and interpretation of data related to baseline quality improvement and patient safety knowledge in interns at the University of Florida. Data will be used towards needs assessment in development of the QI/PS curriculum for housestaff. Additional opportunities for scholarship in graduate medical education available.

Project Title: Machine Learning to Predict Cancer

Faculty Mentor’s Name: Dr. Christopher Cogle
Phone: 352-273-7493
Email: christopher.cogle@medicine.ufl.edu

Student’s Name: Yujia Zhou
Email: yzhou1996@ufl.edu

Project Description:

We hypothesize that University of Florida (UFL) clinical data with approximate one million electronic patient health records (EHR) can be analyzed by deep reinforcement learning (RL) for predictions of early cancer diagnoses.

In this project we will (Aim 1) analyze UFL data of cancer and non-cancer cases using established national and international diagnostic guidelines to compute clinical rules for diagnosing and detecting multiple myeloma, breast cancer and pancreatic cancer. In Aim 2, we will process the data and formalize forward and inverse RL environments for diagnosing cancers. Where one RL formulation contains UFL cases of cancer and non-cancer and the agent interacts with the EHR environment at each timestep iteratively exploring and learning associations and policies between novel health events, diagnoses and outcomes for individual patients. Learned policies will be examined and compared to conventional cancer diagnosis guidelines from Aim 1.

Project Title: Precision Oncology by CRISPR Screening

Faculty Mentor’s Name: Dr. Christopher Cogle
Phone: 352-273-7493
Email: christopher.cogle@medicine.ufl.edu

Student’s Name: David King
Email: djking0402@ufl.edu

Project Description:

Students will use a CRISPR-Cas9 system to define gene and gene combinations that drive leukemia cell survival and proliferation. The student will then design drug or drug combination that mimics the gene deletions, and then test those drugs on the leukemia cells. If the drug or drug combination is effective at killing leukemia cells, then patients with leukemia will receive the drugs in a clinical trial setting.

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