Jessica Patricoski, MS
Computational Biology PhD Student
✉️ jessica_patricoski@brown.edu
📖 Brown University - Center for Computational Molecular Biology
🧬 Uzun Translational Bioinformatics Lab
📍 Providence, RI
EDUCATION
Brown University, PhD
Computational Biology | 2022 - Present
Uzun Translational Bioinformatics Lab
Advisor: Ece Gamsiz Uzun, MS, PhD, FAMIA
The Johns Hopkins University School of Medicine, MS
Health Sciences Informatics Research | 2020 - 2022
Advisor: Taxiarchis Botsis, PhD, MS
Texas Christian University, BA
Mathematics, cum laude | 2015 - 2020
PUBLICATIONS
Graduate
Ting H, Belouali A, Patricoski J, Lehmann H, et al. Trends and opportunities in computable clinical phenotyping: A scoping review. J Biomed Inform. 2023. doi: 10.1016/j.jbi.2023.104335
Patricoski J, Kreimeyer K, Balan A, Hardart K, et al. An evaluation of pretrained BERT models for comparing semantic similarity across unstructured clinical trial texts. Stud Health Technol Inform. 2022. doi: 10.3233/SHTI210848
Krachman JA*, Patricoski JA*, Le CT*, Park J*, Zhang J*, et al. Predicting flow rate escalation for pediatric patients on high flow nasal cannula using machine learning. Front Pediatr. 2021. doi: 10.3389/fped.2021.734753 (*Shared first-authors)
Undergraduate
Ghaly R, Haroutunian A, Grigoryan G, Patricoski JA, et al. Management of CRPS secondary to preganglionic c8 nerve root avulsion: A case report and literature review. Surg Neurol Int. 2020. doi: 10.25259/SNI_318_2020
Ghaly RF, Haroutunian A, Khamooshi P, Patricoski J, et al. Recent decline in the use of invasive neurocritical care monitoring for traumatic brain injury: A case report. Surg Neurol Int. 2020. doi: 10.25259/SNI_65_2020
ABOUT ME
I'm a 3rd-year PhD Candidate at Brown University under the advisement of Dr. Ece Uzun. My work primarily concerns predictive cancer modeling using genomic data and various machine and deep learning algorithms. Initially inspired by my experiences working in neurology & pediatric clinical care, I found my passion in developing tools that utilize cutting-edge computational methods to advance antineoplastic therapies and improve patient outcomes.
Feel free to check out the Uzub Lab website for additional research happening in the lab.
Interests
Cancer informatics
Machine learning
Deep learning
Pharmacogenomics
Programming languages
Python
Java
SQL
MATLAB
Bash
R
I also speak conversational Spanish, have two cats, and enjoy building LEGOs.
RESEARCH PROJECTS
Brown University - Center for Computational Molecular Biology
C2RCF: Development of Clinically Relevant Knowledge-Based Database Using NLP | 10/23 - Present
PIs: Ece Gamsiz Uzun, MS, PhD, FAMIA & Jeremy Warner MD, MS, FAMIA, FASCO
LUNAR: Deep Learning Applications in Cancer Recurrence | 06/23 - Present
PI: Ece Gamsiz Uzun, MS, PhD, FAMIA
Automation of Data Cleaning and Initial Analysis for MIP K13 Haplotype Analysis | 02/23 - 05/23
PI: Jeff Bailey, MD, PhD
Johns Hopkins University School of Medicine - Biomedical Informatics & Data Science
Trends and Opportunities in Computable Clinical Phenotyping: A Scoping Review | 10/21 - 05/22
PI: Taxiarchis Botsis, PhD, MS
The Johns Hopkins Molecular Tumor Board: Using Genomic Alterations and Biomarkers to Match Cancer Patients with Targeted Therapy Clinical Trials| 05/21 - 05/22
Collaboration with the Sidney Kimmel Comprehensive Cancer Center
PI: Taxiarchis Botsis, PhD, MS
Improving Data Quality in an Institutional Clinical Trial Data Repository to Support Patient-Trial Matching (thesis) | 05/21 - 03/22
Collaboration with the Sidney Kimmel Comprehensive Cancer Center
PI: Taxiarchis Botsis, PhD, MS
Extraction of COVID-19 Vaccine Adverse Events Using Natural Language Processing | 03/21 - 05/21
PI: Hongfang Liu, MS, PhD & Liwei Wang, MD, PhD
Johns Hopkins University School of Medicine - Molecular Biology & Genetics
Using the Reciprocal Best Hit Method to Find Potentially Orthologous Promoter Regions Between Homo sapiens GRCh38.p13 and Mus musculus GRCm39 – A Health Sciences Informatics Independent Study | 03/21 - 05/21
PI: Sarah Wheelan, MD, PhD
Johns Hopkins University - Department of Biomedical Engineering; Institute for Computational Medicine
Predicting Flow Rate Escalation for Pediatric Patients on High Flow Nasal Cannula Using Machine Learning | 08/20 - 10/21
PIs: Raimond Winslow, PhD; Joseph Greenstein, PhD; Jules Bergmann, MD; James Fackler, MD; and Anthony Sochet, MD
Ghaly Neurosurgical Associates
Recent Decline in the Use of Invasive Neurocritical Care Monitoring for Traumatic Brain Injury: A Case Report | 01/19 - 02/20
Management of CRPS Secondary to Preganglionic C8 Nerve Root Avulsion: A Case Report and Literature Review | 01/18 - 05/20
Intracranial Subdural Hematoma: A Rare but Feared Complication of Obstetric Epidural Analgesia | 01/18 - 08/19
Limited Spine Surgery Can Be Utilized as an Adjuvant to Reduce the Opioid-Based Management in Patients with Adult-Onset Scoliosis (AOS) and Complex Spine Disorders | 06/17 - 05/18
Resolution of Chronic Hypertension Following Spinal Decompression: Is Chronic Spinal Cauda Equina Compression as a Result of Advanced Spondyloarthropathy a Reversible Cause of Chronic Hypertension? | 06/17 - 01/18
PI: Ramsis F. Ghaly, MD, FACS (all projects at Ghaly Neurosurgical Associates)
CONFERENCE PRESENTATIONS & POSTERS
Patricoski JA, Warner JL, Gamsiz Uzun ED. Predicting recurrence of low-grade glioma - A deep learning approach. Poster presented at: 2024 American Medical Informatics Association Informatics Summit; Mar 2024; Boston, MA.
Patricoski JA, Warner JL, Gamsiz Uzun ED. Predicting recurrence of low-grade glioma - A deep learning approach. Poster presented at: Legorreta Cancer Center Retreat; Sep 2023; Providence, RI.
Wang L, He H, Mathur S, Li Z, Akinseye A, Hamal M, Patricoski JA, et al. Extraction of COVID-19 vaccine adverse events using natural language processing. Poster presented by Wang at: 2022 American Medical Informatics Association Informatics Summit; Mar 2022; Chicago, IL.
Patricoski JA, Kreimeyer K, Balan A, Hardart K, et al. An evaluation of pretrained BERT models for comparing semantic similarity across unstructured clinical trial texts. Paper presented at: 19th International Conference on Informatics, Management and Technology in Healthcare; Oct 2021; Athens, Greece [virtual].
Krachman J, Patricoski JA, Le C, Park J, Zhang J. Using advanced machine learning models to predict flow rate escalation for pediatric patients on high flow nasal cannula. Poster presented by Krachman at: Johns Hopkins Engineering Design Day 2021; May 2021; Baltimore, MD [virtual].
TEACHING & WORK EXPERIENCE
Brown University - Division of Biology and Medicine
Graduate Teaching Assistant | 01/24 - Present
BIOL 1540/2540 (Molecular Genetics)
Johns Hopkins Molecular Tumor Board
Informatics Team Graduate Researcher | 05/21 - 03/22
PI: Taxiarchis Botsis, PhD, MS
Johns Hopkins University - Department of Computer Science
Graduate Teaching Assistant | 03/21 - 03/22
EN.601.402 (Digital Health and Biomedical Informatics)
Johns Hopkins University - Department of Molecular Biology & Genetics
Graduate Teaching Assistant | 03/21 - 03/22
EN.601.402 (Digital Health and Biomedical Informatics)
Ghaly Neurosurgical Associates
Neurosurgical Research Intern | 06/17 - 05/20
PI: Ramsis Ghaly, MD, FACS
UNIVERSITY LEADERSHIP
Public Relations Committee Member, JHU SOM Graduate Student Association | 09/21 - 05/22
Program Representative, JHU SOM Graduate Student Association | 08/21 - 05/22
President, TCU Math Club | 04/18 - 04/20
Founding Member & Treasurer, TCU Students Acting for Gender Equity Treasurer | 04/18 - 04/20
Vice President of Marketing and Digital Media, TCU Young Democratic Leaders | 05/17 - 01/19
Founding Member & Vice President of Event Coordination, TCU Young Democratic Leaders | 05/16 - 05/17
SELECT HONORS & AWARDS
Pastiche Pie Award, Brown University CSCI 2810 Advanced Computational Molecular Biology | 12/22
Best Student Paper, 19th International Conference on Informatics, Management and Technology in Healthcare | 10/21
GSA Representative Faculty Nomination, JHU SOM Biomedical Informatics and Data Science | 08/21
Pi Mu Epsilon Faculty Nomination, TCU Department of Mathematics | 03/20
SELECT PROFESSIONAL MEMBERSHIPS
American Medical Informatics Association (AMIA) | 02/24 - Present
Brown Center for Clinical Cancer Informatics and Data Science (CCIDS) | 06/23 - Present
Pi Mu Epsilon (National Mathematics Honor Society) | 03/20 - Present
American Mathematical Society | 08/19 - Present
VOLUNTEER WORK
Meals from the Heart Panhellenic Volunteer, Ronald McDonald House Fort Worth | 09/15 - 04/19
Clinical Reception & Administrative Staff, Naperville Pediatric Associates | 06/17 - 08/17
Teaching Assistant (laparoscopic surgery), Dr. Rubin's Mini Medical School | 06/17 - 07/17