Webinar: The Use of Natural Language Processing to Improve Phenotype Extraction for Precision Medicine

October 24, 2019
Venue: Online Webinar

When: Thursday 24th October 2019

Time: 3:00pm BST; 4:00pm CEST; 11:00am EDT; 8:00am PDT

Duration: 60 minutes.

"The Use of Natural Language Processing to Improve Phenotype Extraction for Precision Medicine - University of Iowa NLP-Based Phenome Extraction from the EHR"


Precision medicine focuses on disease treatment and prevention, taking into account the variability in genes, environment, and lifestyle between individual patients. In order to understand the best treatment pathway for a particular patient or group of patients, it is important to be able to access and analyze detailed information from the medical records of patients, and ideally broader aspects beyond their medical history.

Clinical genomic testing (e.g. chromosome microarray, gene panel testing, exome/genome sequencing) is performed on thousands of patients annually and relies heavily on manual chart review by a healthcare professional to identify the patient's clinical phenotype. Natural language processing (NLP) is being used to obtain high-quality comprehensive phenotype information from the electronic medical record for patients who have undergone clinical genomic testing. While this project is still on-going, the work has the potential to aid in the interpretation of genetic test results, and to directly improve the diagnosis and clinical care of patients seen at the University of Iowa Stead Family Children's Hospital.

Learning Objectives
80% of EHR data is unstructured but has many insights locked in clinical notes. Researchers and clinicians need a way to rapidly search and extract key information to use in clinical research and improved care. Learn how NLP is being used to transform unstructured source data into clinical and research decision support insights:

  • Phenotypic characteristics are often extracted by exhaustive manual chart review, find out how NLP can reduce this time significantly
  • Understand how EHR data can be exported and used in NLP systems, what issues to expect
  • Explore the training and evaluation of NLP results to achieve high levels of accuracy


Benjamin Darbro, MD, PhD

Dr. Darbro is an Associate Professor of Pediatrics within the Stead Family Department of Pediatrics at the University of Iowa. Dr. Darbro received his undergraduate degree in Biochemistry and Molecular Biology from Nebraska Wesleyan University. He received his M.D. and Ph.D in Molecular and Cellular Biology at the University of Iowa. Dr. Darbro is board certified in both Clinical and Molecular Genetic Pathology and is currently the Director of the Shivanand R. Patil Cytogenetics and Molecular Laboratory. Dr. Darbro’s primary research interest is in the genetic determinants of neurodevelopmental disorders, molecular mechanisms of cancer, and how the two seemingly unrelated conditions overlap at a genetic-network level. He studies the roles of both germline and somatic sequence level and structural variations in the context of a “genomic mutational burden” hypothesis of both cancer and neurodevelopmental disorders.

Alyssa Hahn

Alyssa Hahn is a doctoral student in the Interdisciplinary Graduate Program in Genetics at the University of Iowa under the direction of Dr. Benjamin Darbro. She earned her Bachelors' degree in Biochemistry & Molecular Biology at Cornell College, and participated in two undergraduate summer research program studying the molecular mechanisms of metal trafficking and and copy number variants. Her doctoral research is focused on evalutating the pathogenicity of copy number variants, and providing insight into the genes and/or gene networks that are important to a clinical phenotype.