> [!info] > I've been involved with many research projects over the past 10 years in the capacity of a data scientist and data engineer. These projects have allowed me to further hone my skills and learn to work with new toolsets while solving the unique problems that came up with each project. ## Clinical Decision Support using Large Language Models - Description: Assessing the capabilities of OpenAI’s large language models (e.g., DaVinci GPT3.5 and GPT4) for the purposes of clinical decision support in the field of hematopathology. - Tools utilized: Python, natural language processing, OpenAI API ## Thyroid Tele-Cytology Rapid Onsite Evaluation - Description: Evaluating causes for erroneous inadequate diagnoses on remote rapid onsite evaluation of thyroid specimen while using tele-cytology. - Tools utilized: Anaconda statistics libraries, Python, Pandas. ## Bone Specimen Inadequacy Rates at Rapid Onsite Evaluations - Description: Evaluating the proportion of bone specimen that are called non-diagnostic at the time of rapid onsite evaluation, when compared to all other specimen over a period of 8 years. - Tools utilized: large dataset analysis using Python, Pandas and natural language processing to parse thousands of pathology reports ## Breast Predictive Marker Analysis for CAP Inspections         - Description: Parsing thousands of breast pathology reports (biopsies and/or resections) for purposes of assessing predictive marker statuses and generating a report for College of American Pathologists annual inspection - Tools utilized: large dataset analysis using Python, Pandas and natural language processing to parse thousands of pathology reports ## Software to interact with New York Statewide Medical Database    - Description: Creating a software with GUI for medical research staff (medical students, residents, fellows) can access the database for purposes of research project development - Tools utilized: Python, Tkinter, SQL