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Caitlin Dreisbach, PhD, RN

Caitlin Dreisbach, PhD, RN

(Pronouns: She/her)
  • Assistant Professor


  • Postdoctoral Fellowship, 2022. The Data Science Institute at Columbia University. New York, NY
  • PhD in Nursing, 2020. University of Virginia. Charlottesville, VA
  • Master's of Science in Data Science, 2018. University of Virginia. Charlottesville, VA
  • Bachelor's of Science in Nursing, 2013. Johns Hopkins University. Baltimore, MD
  • Bachelor's of Science, 2012. Cornell University. Ithaca, NY


Caitlin Dreisbach, PhD, RN, is an assistant professor at the University of Rochester School of Nursing with an affiliation in the Goergen Institute for Data Science. Dreisbach completed a two-year postdoc at the Columbia University Data Science Institute prior to joining the faculty. 

Her research focus is on the use of quantitative methods to make better clinical assessments during pregnancy. As a former labor and delivery nurse, Dreisbach is interested in reimagining the current state of technology use during labor and delivery. In combination with the real-world experiences of birthing people, Dreisbach aims to enhance the care clinicians provide at the bedside.

Affiliated Faculty, University of Rochester Goergen Institute for Data Science, Rochester, NY. 2022 - Current

Assistant Professor (Tenure-Track), University of Rochester School of Nursing, Rochester, NY. 2022 - Current

Postdoctoral Research Scientist, Data Science Institute at Columbia University (Data science), New York, NY. 7/2020 - 6/2022

Pre-doctoral student, University of Virginia (Nursing), Charlottesville, VA. 8/2015 - 5/2020
Josephine Craytor Nurse Faculty Award
University of Rochester, 2024

Most Promising New Investigator
University of Rochester, 2023

Phyllis J. Verhonick Dissertation Award
University of Virginia School of Nursing, 2020

Wood Family Award for Outstanding Service in Data Science
Data Science Institute, University of Virginia, 2018

The Raven Society Member
University of Virginia, 2017

Graduate Teaching Assistant Award
University of Virginia School of Nursing, 2017

Beginning Practitioner of the Year Nomination
University of Virginia Medical Center, 2016

Intramural Research Training Award
National Institute of Nursing Research Summer Genetics Institute (SGI), 2016

Sigma Theta Tau Nursing Honor Society, Beta Kappa Chapter
University of Virginia School of Nursing, 2016

The Church Home and Hospital Nursing Alumnae Award
The Johns Hopkins University, 2013

BSN Graduation Class speaker
The Johns Hopkins University, School of Nursing, 2013

Lambda Pi Eta National Communication Honor Society
Cornell University, 2012
A critical review of social determinants of health in chronic condition symptom cluster research
Koleck, T. A., Patzak, S. A., Dziewulski, G., Shen, L., Lor, M., Conway, A., & Grayson, S. C.
Podium presentation at the Council for the Advancement of Nursing Science 2022 State of the Science Congress on Nursing Research: Social & Structural Determinants of Health, 2022
Washington, District Of Columbia

“Data-Informed Women’s Health: Data Science and the Microbiome.”
Precision Health (T32) Methodology Summer Boot Camp, University of Texas at Austin, 2022

“Clustering and Validation of COVID-19 Symptom Phenotypes for Hispanic/Latina Women”
South, K. Koleck, T., Barcelona, V., Elhadad, E., Mamykina, O., & Bakken, S.
American College of Obstetricians and Gynecologists (ACOG), 2021 ACOG Annual Clinical and Scientific Meeting (ACSM): Personalizing Care: A Way to the Future, 2021

“Informing Symptom Science Using a Citizen Science Application in the COVID-19 Pandemic"
South, K. Koleck, T., Barcelona, V., Elhadad, E., Mamykina, O., & Bakken, S.
2021 Annual Symposium, American Medical Informatics Association (AMIA), 2021
San Diego, California

“Data-informed women's health: from the microbiome to symptom-focused artificial intelligence.”
Columbia University School of Nursing, 2020

“Maternal Microbiome & the Environment: What is our role as nurses and scientists?”
University of Calgary, 2020

“The Uses of Data in Patient Care.”
Deas, K., & Gabrielle, A.
Tom Tom Cities Rising Summit, 2020
Charlottesville, Virginia

“The influence of maternal obesity on microbial function and impaired glucose tolerance during pregnancy.”
Mculloch, J., Prescott, S., Dudley, D., Trinchieri, G., Alhusen, J., & Siega-Riz, AM.
International Society of Nurses in Genetics 2019 World Congress “Transforming Health through Genomic Nursing”, 2019
San Antonio, Texas

“Perception of Psychological Trauma in Labor and Delivery”
Schminkey, D., Suphal, K., Thelen, M., Dunbar, P., & Price, J.
Evidence-Based Practice Day, University of Virginia Health System, 2019
Charlottesville, Virginia

“Influence of maternal obesity and excessive gestational weight gain on maternal and child microbiomes: a systematic review.”
Prescott, S., & Alhusen, J.
Barbara Parker Research Symposium, 2019
Charlottesville, Virginia

“Postpartum assessment of psychological trauma from the labor and delivery experience.”
M. Thelen., C.P. Muthusubramanian, F. Tyree, K. Suphal, B. Morrill, C. Miller-Davis, & L. Letzkus
Association for Women’s Health, Obstetric, and Neonatal Nurse (AWHONN), Virginia Section, 2019
Charlottesville, Virginia

“Keynote Session: The State of Data Science.”
T. Koleck
2018 World Congress “Building Connections to Genomic Health.”, International Society for Nurses in Genetics (ISONG), 2018
Orlando, Florida

“Joining Separate Paradigms: Text Mining and Deep Neural Networks to Characterize Neuronal Cell Type in the Cortex and Hippocampus.”
Wall, M., Zaidi, A., Flower, A., & Overall, C.
TomTom Machine Learning Conference, 2018
Charlottesville, Virginia

“Joining Separate Paradigms: Text Mining and Deep Neural Networks to Characterize Neuronal Cell Type in the Cortex and Hippocampus.”
Wall, M., Zaidi, A., Flower, A., & Overall, C.
Systems Information Engineering and Design Conference, 2018
Charlottesville, Virginia

“Text Mining and Deep Neural Networks to Characterize Neuronal Cell Type in the Cortex and Hippocampus.”
Wall, M., Zaidi, A., Flower, A., & Overall, C.
Barbara Parker Research Symposium, 2018
Charlottesville, Virginia

“Predictors of Gestational Weight Gain in a Population-based Sample.”
Alhusen, J., Seiga-Riz, A.M., Constantoulakis, L, & Geller, R.
Graduate School of Arts and Sciences Huskey Research Symposium, University of Virginia, 2017
Charlottesville, Virginia
Meng, Y., Thornburg, L., Dreisbach, C., Orzolek, C., Kautz, A., Murphy, H., Rivera- Núñez, Z., Wang, C., Miller, R., O'Connor, T., & Barrett, E. (2024). The role of prenatal maternal sex steroid hormones in weight and adiposity at birth and growth trajectories during infancy. Research Square. DOI: 10.21203/

Dreisbach, C., Karunanidhi, A.P., Shimazaki, Y., Rana, N., Thornburg, L., Wang, L., Groth, S.& Hollenbach, S. (2023). Using Simulated Data to Predict Birthweight from Prenatal Ultrasound Images. 2023 IEEE Western New York Image and Signal Processing Workshop, WNYISPW 2023. DOI: 10.1109/WNYISPW60588.2023.10349465

Dreisbach, C., Prescott, S., Siega-Riz, A.M., McCulloch, J., Habermeyer, L., Dudley, D., Trinchieri, G., Kelsey, C., & Alhusen, J. (2023). Composition of the maternal gastrointestinal microbiome as a predictor of neonatal birth weight. Pediatric Research. PMID: 37029236 DOI: 10.1038/s41390-023-02584-4

Hobensack, M., Dreisbach, C., Topaz, M., Elhadad, N., Mamykina, O., & Bakken, S.B. (2023). Older Adult Engagement With Symptom Reporting in a COVID-19 Citizen Science Application. Journal of Gerontological Nursing, 49 (4), 6-11. DOI: 10.3928/00989134-20230309-02

Idnay, B., Fang, Y., Dreisbach, C., Marder, K., Weng, C., & Schnall, R. (2023). Clinical research staff perceptions on a natural language processing-driven tool for eligibility prescreening: An iterative usability assessment. International Journal of Medical Informatics. PMID: 36638583 PMCID: PMC9912278 DOI: 10.1016/j.ijmedinf.2023.104985

Le, J., Alhusen, J., & Dreisbach, C. (2023). Screening for Partner Postpartum Depression: A Systematic Review. MCN: The American Journal of Maternal/Child Nursing. PMID: 36744867 DOI: 10.1097/NMC.0000000000000907

Bernstein, S., Frederick, A., Abbu, S., Condo DiCioccio, H., Thomas, A., & Dreisbach, C. (2023). Reflections on the 2021 MCN Editorial Fellowship. MCN: The American Journal of Maternal/Child Nursing, 48 (1), 6-7. PMID: 36469891 DOI: 10.1097/NMC.0000000000000872

Dreisbach, C., Alhusen, J., Prescott, S., Dudley, D., Trinchieri, G., & Siega-Riz, A. M. (2022). Metagenomic characterization of the maternal prenatal gastrointestinal microbiome by pregravid BMI. Obesity. PMID: 36562201 DOI: 10.1002/oby.23659

Dreisbach, C., Wright, M.L., Walker, R.K., Byon, H.D., & Keim-Malpass, J. (2022). Nursing science as a federally-recognized STEM degree: A call to action for the United States with global implications. International Journal of Nursing Studies Advances, 4, 100084. DOI: 10.1016/j.ijnsa.2022.100084

Dreisbach, C., Prescott, S., Alhusen, J., Dudley, D., Trinchieri, G., & Siega-Riz, A.M. (2022). Association between microbial composition, diversity, and function of the maternal gastrointestinal microbiome with impaired glucose tolerance on the glucose challenge test. PLOS ONE. PMID: 36584051 PMCID: PMC9803092 DOI: 10.1371/journal.pone.0271261

Bakken, S., & Dreisbach, C. (2022). Informatics and data science perspective on Future of Nursing 2020–2030: Charting a pathway to health equity. Nursing Outlook. PMID: 36446542 DOI: 10.1016/j.outlook.2022.04.004

South, K., Bakken, S., Koleck, T., Barcelona, V., Elhadad, N., & Dreisbach, C. (2022). Women’s Experiences of Symptoms of Suspected or Confirmed COVID-19 Illness During the Pandemic. Nursing for Women's Health. PMID: 36265561 PMCID: PMC9575040 DOI: 10.1016/j.nwh.2022.09.005

Grayson, S. C., Patzak, S. A., Dziewulski, G., Shen, L., Dreisbach, C., Lor, M., Conway, A., & Koleck, T. A. (2022). Moving beyond Table 1: A critical review of the literature addressing social determinants of health in chronic condition symptom cluster research. Nursing Inquiry (12519). PMID: 36283980 DOI: 10.1111/nin.12519

Prescott,S., Schminkey, D., Abukhalaf, D., DeGuzman, P., & Dreisbach, C. (2022). A framework to guide research and practice response to emerging infectious diseases: Genomic-to-global considerations.. Public health nursing (Boston, Mass.). PMID: 36128924 DOI: 10.1111/phn.13133

Dreisbach, C., Grayson, S., Leggio, K., Conway, A., & Koleck, T. (2022). Predictors of unrelieved symptoms in All of Us Research Program participants with chronic conditions. Journal of Pain and Symptom Management. PMID: 36096320 DOI: 10.1016/j.jpainsymman.2022.08.018

Ford, S., Merchant, R., Pavuloori, A., Williams, R., Dreisbach, C., Saunders, A., Wernz, C., & Michel, J. (2022). Patient Phenotypes to Identify Resource Allocation and Usage in Primary Care. 2022 Systems and Information Engineering Design Symposium (SIEDS). DOI: 10.1109/sieds55548.2022.9799406

Dreisbach, C., Morgan, H., Cochran, C., Gyamfi, A., Henderson, W.A., & Prescott, S. (2022). Metabolic and Microbial Changes Associated With Diet and Obesity During Pregnancy: What Can We Learn From Animal Studies?. Frontiers in Cellular and Infection Microbiology, 11. PMID: 35118010 PMCID: PMC8804207 DOI: 10.3389/fcimb.2021.795924

Fleming, M., Dondeti, P., Dreisbach, C., & Poliak, A. (2021). Fine-Tuning Transformers for Identifying Self-Reporting Potential Cases and Symptoms of COVID-19 in Tweets. . DOI: 10.48550/ARXIV.2104.05501

Prescott, S., Dreisbach, C., Baumgartel, K., Koerner, R., Gyamfi, A., Canellas, M., St. Fleur, A., Henderson, W.A., & Trinchieri, G. (2021). Impact of Intrapartum Antibiotic Prophylaxis on Offspring Microbiota. Frontiers in Pediatrics, 9. PMID: 34956974 PMCID: PMC8703107 DOI: 10.3389/fped.2021.754013

Barcelona, V., Montalvo-Ortiz, J.L., Wright, M.L., Nagamatsu, S.T., Dreisbach, C., Crusto, C.A., Sun, Y.V. & Taylor, J.Y. (2021). DNA methylation changes in African American women with a history of preterm birth from the InterGEN study. BMC Genomic Data, 22 (1). PMID: 34482817 PMCID: PMC8418749 DOI: 10.1186/s12863-021-00988-x

Idnay, B., Dreisbach, C., Weng, C., & Schnall, R. (2021). A systematic review on natural language processing systems for eligibility prescreening in clinical research. Journal of the American Medical Informatics Association. PMID: 34725689 PMCID: PMC8714283 DOI: 10.1093/jamia/ocab228

Rohan, A., Adams, E.D., Dreisbach, C., & Frederick, A. (2021). Toward Evidence-Based Practice. MCN: The American Journal of Maternal/Child Nursing, 46 (6), 364-366. DOI: 10.1097/nmc.0000000000000770

Dreisbach, C. (2021). Reimagining and Contextualizing Fetal Weight Estimation. MCN: The American Journal of Maternal/Child Nursing, 46 (6), 368-368. PMID: 34653039 DOI: 10.1097/NMC.0000000000000764

Kelsey, C. M., Prescott, S., McCulloch, J. A., Trinchieri, G., Valladares, T. L., Dreisbach, C., Alhusen, J., & Grossmann, T. (2021). Gut microbiota composition is associated with newborn functional brain connectivity and behavioral temperament. Brain, Behavior, and Immunity, 91, 472-486. PMID: 33157257 DOI: 10.1016/j.bbi.2020.11.003

Dreisbach, C., & Koleck, T. A. (2020). The State of Data Science in Genomic Nursing. Biological Research For Nursing, 109980042091599. PMID: 32266827 PMCID: PMC7492779 DOI: 10.1177/1099800420915991

Dreisbach, C. (2020). The Influence of Maternal Obesity on Microbial Function and Impaired Glucose Tolerance during Pregnancy. Association of Womens Health, Obstetric & Neonatal. DOI: 10.18130/v3-pg7b-e298

Dreisbach, C., Prescott, S., & Alhusen, J. (2020). Influence of Maternal Prepregnancy Obesity and Excessive Gestational Weight Gain on Maternal and Child Gastrointestinal Microbiome Composition: A Systematic Review. Biological Research For Nursing, 109980041988061. PMID: 31597472 PMCID: PMC7140212 DOI: 10.1177/1099800419880615

Crowder, J., Burnett, C., Laughon, K., & Dreisbach, C. (2019). Elder Abuse in American Indian Communities: An Integrative Review. Journal of Forensic Nursing, 15 (4), 250-258. PMID: 31764529 DOI: 10.1097/JFN.0000000000000259

Tallon, E., & Dreisbach, C. (2019). Using Data Science to Understand Complexity and Quantify Heterogeneity in the Onset and Progression of Chronic Disease. Biological Research For Nursing, 21 (5), 449-457. PMID: 31345047 DOI: 10.1177/1099800419863161

Dreisbach, C., Koleck, T.A., Bourne, P.E., & Bakken, S. (2019). A systematic review of natural language processing and text mining of symptoms from electronic patient-authored text data. International Journal of Medical Informatics, 125, 37-46. PMID: 30914179 PMCID: PMC6438188 DOI: 10.1016/j.ijmedinf.2019.02.008

Kelsey, C., Dreisbach, C., Alhusen, Jeanne, A., & Grossmann, T. (2019). A primer on investigating the role of the microbiome in brain and cognitive development. Developmental Psychobiology, 61 (3), 341-349. PMID: 30315569 DOI: 10.1002/dev.21778

Koleck, T.A., Dreisbach, C., Bourne, P.E., & Bakken, S. (2019). Natural language processing of symptoms documented in free-text narratives of electronic health records: a systematic review. Journal of the American Medical Informatics Association, 26 (4), 364-379. PMID: 30726935 PMCID: PMC6657282 DOI: 10.1093/jamia/ocy173

Turrentine, F.E., Dreisbach, C., St Ivany, A.R., Hanks, J.B., & Schroen, A.T. (2019). Influence of Gender on Surgical Residency Applicants’ Recommendation Letters. Journal of the American College of Surgeons, 228 (4), 356-365e3. PMID: 30630084 DOI: 10.1016/j.jamcollsurg.2018.12.020

Turner, A.W., Wong, D., Khan, M.D., Dreisbach, C., Palmore, M., & Miller, C.L. (2019). Multi-Omics Approaches to Study Long Non-coding RNA Function in Atherosclerosis. Frontiers in Cardiovascular Medicine, 6. PMID: 30838214 PMCID: PMC6389617 DOI: 10.3389/fcvm.2019.00009

Harrison, E., Dreisbach, C., Basit, N., & Keim-Malpass, J. (2018). An Application of Data Mining Techniques to Explore Congressional Lobbying Records for Patterns in Pediatric Special Interest Expenditures Prior to the Affordable Care Act. Frontiers in Big Data, 1. PMID: 33693319 PMCID: PMC7931899 DOI: 10.3389/fdata.2018.00003

Nobles, A.L., Dreisbach, C., Keil-Malpass, J., & Barnes, L.E. (2018). "Is this a STD? Please help!": Online Information Seeking for Sexually Transmitted Diseases on Reddit.. Proceedings of the ... International AAAI Conference on Weblogs and Social Media. International AAAI Conference on Weblogs and Social Media. PMID: 30984474 PMCID: PMC6460917

Turner, A.W., Wong, D., Dreisbach, C., & Miller, C.L. (2018). GWAS Reveal Targets in Vessel Wall Pathways to Treat Coronary Artery Disease. Frontiers in Cardiovascular Medicine, 5. PMID: 29988570 PMCID: PMC6026658 DOI: 10.3389/fcvm.2018.00072

Wall, M., Dreisbach, C., Zaidi, A., Flower, A., & Overall, C. (2018). Using autoencoders and text mining to characterize single cell populations in the hippocampus and cortex. 2018 Systems and Information Engineering Design Symposium (SIEDS). DOI: 10.1109/sieds.2018.8374718

Trowbridge, E.R., Dreisbach, C., Sarosiek, B.M., Dunbar, C.P., Evans, S.L., Hahn, L.A., & Hullfish, K.L. (2018). Review of enhanced recovery programs in benign gynecologic surgery. International Urogynecology Journal, 29 (1), 3-11. PMID: 28871417 DOI: 10.1007/s00192-017-3442-0

Alhusen, J.L., Geller, R., Dreisbach, C., Constantoulakis, L., & Siega-Riz, A.M. (2017). Intimate Partner Violence and Gestational Weight Gain in a Population-Based Sample of Perinatal Women. Journal of Obstetric, Gynecologic & Neonatal Nursing, 46 (3), 390-402. PMID: 28294945 PMCID: PMC5423819 DOI: 10.1016/j.jogn.2016.12.003

Niederdeppe, J., Roh, S., & Dreisbach, C. (2016). How Narrative Focus and a Statistical Map Shape Health Policy Support Among State Legislators. Health Communication, 31 (2), 242-255. PMID: 26086340 DOI: 10.1080/10410236.2014.998913

Neural Network Approach to Estimate Fetal Weight in the Late Third Trimester of Pregnancy
8/17/2022 - 7/31/2025
Role: Principal Investigator

Significance of Symptom Onset-To-Angiography Time in Non-ST-Segment Elevation Myocardial Infarction
7/1/2023 - 6/30/2024
Role: Consultant: Data Scientist
PI: Sukardi Suba, PhD, RN
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