Rochester, Minnesota




Sunghwan Sohn, Ph.D., has expertise in mining large-scale electronic health records (EHRs) to unlock unstructured and hidden information using natural language processing and machine learning. Dr. Sohn's research goal is to develop strategies for how to best use informatics from precision medicine to population health in order to achieve better patient solutions.

Focus areas

  • Information extraction and normalization. Dr. Sohn applies natural language processing techniques to extract unstructured medical concepts from clinical narratives and map them to standard forms in order to facilitate clinical research and information exchange across health care institutions.
  • Patient cohort identification. Dr. Sohn develops algorithms to identify patient cohorts with specific medical conditions (such as peripheral artery disease, abdominal artery aneurysm, falls, delirium or asthma) by mining various EHRs to enable large-scale epidemiologic study.
  • The use of routinely collected EHRs for early detection of cognitive impairment. Dr. Sohn is interested in analyzing temporal trends in patient health conditions obtained from EHR documents to identify patients with (or those with high risk of) cognitive impairment, augmenting cognitive assessment and screening.
  • Secondary use of EHRs to improve clinical competency and education. Dr. Sohn is developing an informatics tool to assess clinicians' adherence to asthma guidelines, providing personal clinical effectiveness data. This can help residents in achieving clinical competence in asthma care and documentation.
  • Transportable clinical neurolinguistic processing (NLP) tools. Although clinical NLP systems have proved to be effective for various tasks, their performance often varies across institutions and sources of data. Dr. Sohn is interested in analyzing clinical documentation variations and refining and porting NLP-based tools across different health care institutions through multisite projects such as arthroplasty clinical registries, asthma ascertainment and geriatric syndrome identification.

Significance to patient care

Dr. Sohn's research facilitates the best use of EHRs to solve clinical problems and improve public health. His work provides biomedical scientists and clinicians access to unstructured information from clinical narratives and the clinical text analytics necessary for clinical research and patient care.

Professional highlights

  • Funding recipient, The Eric and Wendy Schmidt Fund for AI Research and Innovation, 2023.


Administrative Appointment

  1. Senior Associate Consultant II-Research, Department of Artificial Intelligence and Informatics

Academic Rank

  1. Associate Professor of Biomedical Informatics


  1. Ph.D. - Engineering Management (Machine Learning Emphasis) Missouri University Of Science & Technology
  2. MS - Computer Engineering University of Missouri, Columbia
  3. BE - Electronics Engineering Kyonggi University

Clinical Studies

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