Masoud Rouhizadeh

Masoud Rouhizadeh, Ph.D., M.Sc., M.A.

Assistant Professor

Department: Pharmaceutical Outcomes & Policy
Business Phone: (352) 273-7850
Business Email: mrou@cop.ufl.edu

About Masoud Rouhizadeh

Masoud Rouhizadeh M.A., Prof.MS., M.S., Ph.D. is an Assistant Professor in the University of Florida College of Pharmacy, Department of Pharmaceutical Outcomes, under the AI in the Health Sciences Initiative.

The primary focus of Dr. Rouhizadeh’s research involves applying machine learning and natural language processing methods for identifying clinical concepts from unstructured text and converting them into structured data. Another major part of his research has been developing clinical ontologies and lexical resources, as well as computational models for identifying social and behavioral determinants of health.

Before joining the UF, Dr. Rouhizadeh was a Faculty Instructor at Biomedical Informatics and Data Science and the natural language processing lead at the Institute for Clinical and Translational Research at the Johns Hopkins University School of Medicine. Prior to JHU, he was a postdoctoral fellow at the University of Pennsylvania’s World Well-Being Project and then at the Penn Institute for Biomedical Informatics. He obtained his Master’s and Ph.D. in Computer Science and Engineering from Oregon Health and Science University and his Master’s in Human Language Technology from the University of Trento, Italy.

Research Profile

With a strong foundation in machine learning and natural language processing (NLP), Dr. Rouhizadeh has focused his research on developing large and scalable language analyses with applications to physical, mental, and public health. While much of NLP involves modeling language itself, he builds on such techniques to develop novel approaches to extract clinical concepts from unstructured free-text notes and better understand social and behavioral determinants of health by leveraging the unprecedented amount of data afforded from electronic health records. Another major part of his research has been developing clinical ontologies and lexical resources in various domains, as well as computational models for identifying signs of neurological disorders affecting children and the elderly.

Open Researcher and Contributor ID (ORCID)

0000-0002-9006-6112

Publications

2021
Analysis of Primary Care Provider Electronic Health Record Notes for Discussions of Prediabetes Using Natural Language Processing Methods.
Journal of general internal medicine. [DOI] 10.1007/s11606-020-06400-1. [PMID] 33469758.
2021
Assessing the Impact of Social Needs and Social Determinants of Health on Health Care Utilization: Using Patient- and Community-Level Data.
Population health management. 24(2):222-230 [DOI] 10.1089/pop.2020.0043. [PMID] 32598228.
2021
COVID-19 SignSym: a fast adaptation of a general clinical NLP tool to identify and normalize COVID-19 signs and symptoms to OMOP common data model.
Journal of the American Medical Informatics Association : JAMIA. 28(6):1275-1283 [DOI] 10.1093/jamia/ocab015. [PMID] 33674830.
2021
Measuring the Value of a Practical Text Mining Approach to Identify Patients With Housing Issues in the Free-Text Notes in Electronic Health Record: Findings of a Retrospective Cohort Study.
Frontiers in public health. 9 [DOI] 10.3389/fpubh.2021.697501. [PMID] 34513783.
2021
Patient Trajectories Among Persons Hospitalized for COVID-19
Annals of Internal Medicine. 174(1):33-41 [DOI] 10.7326/m20-3905.
2020
COVID-19 SignSym: A fast adaptation of general clinical NLP tools to identify and normalize COVID-19 signs and symptoms to OMOP common data model.
ArXiv. [PMID] 32908948.
View on: PubMed
2019
Assessing the Availability of Data on Social and Behavioral Determinants in Structured and Unstructured Electronic Health Records: A Retrospective Analysis of a Multilevel Health Care System
JMIR Medical Informatics. 7(3) [DOI] 10.2196/13802. [PMID] 31376277.
2019
Language impairment in adults with end-stage liver disease: application of natural language processing towards patient-generated health records.
NPJ digital medicine. 2 [DOI] 10.1038/s41746-019-0179-9. [PMID] 31701020.
2015
Measuring idiosyncratic interests in children with autism.
Proceedings of the conference. Association for Computational Linguistics. Meeting. 2015:212-217 [PMID] 29217874.
View on: PubMed
2015
Similarity Measures for Quantifying Restrictive and Repetitive Behavior in Conversations of Autistic Children.
Proceedings of the conference. Association for Computational Linguistics. North American Chapter. Meeting. 2015:117-123 [PMID] 28691123.
View on: PubMed
2014
COMPUTATIONAL ANALYSIS OF TRAJECTORIES OF LINGUISTIC DEVELOPMENT IN AUTISM.
SLT … : … IEEE Workshop on Spoken Language Technology : proceedings. IEEE Workshop on Spoken Language Technology. 2014:266-271 [DOI] 10.1109/SLT.2014.7078585. [PMID] 29057398.
2013
Distributional semantic models for the evaluation of disordered language.
Proceedings of the conference. Association for Computational Linguistics. North American Chapter. Meeting. 2013:709-714 [PMID] 25419547.
View on: PubMed
2012
Automatic detection of pragmatic deficits in children with autism.
The … Workshop on Child, Computer and Interaction. 2012:1-6 [PMID] 28691126.
View on: PubMed
Assessing the Availability of Data on Social and Behavioral Determinants in Structured and Unstructured Electronic Health Records: A Retrospective Analysis of a Multilevel Health Care System (Preprint)
. [DOI] 10.2196/preprints.13802.
Identification of prediabetes discussions in unstructured clinical documentation using natural language processing methods (Preprint)
. [DOI] 10.2196/preprints.29803.

Education

Postdoctoral Training in Computational Social Science and Health Outcomes
2017 · University of Pennsylvania
Ph.D. in Computer Science and Engineering
2015 · Oregon Health and Science University
M.Sc. in Computer Science and Engineering
2013 · Oregon Health and Science University
Professional Master’s in Human Language Technology and Interfaces
2009 · University of Trento
M.A. in Linguistics
2007 · Allameh Tabatabai University

Contact Details

Phones:
Business:
(352) 273-7850
Emails:
Business:
mrou@cop.ufl.edu