Webinar: Efficiency in Clinical Research - Artificial Intelligence - Natural Language Processing (AI-NLP)

May 7, 2020
Venue: Online Webinar

When: Thursday 7th May 2020

Time: 4:00pm BST; 5:00pm CEST; 11:00am EDT; 8:00am PDT.

Duration: 60 minutes.


The traditional ways of doing research isn’t sufficient to keep up with the need of modern medicine in the digital age. The vast amount of data needed to make strides in research is found in both the structured and the unstructured form. However, the majority of the data that is needed for improved outcomes is unstructured and it remains trapped within clinical records. Previously it was necessary for vast amounts of manual labor to be performed to unlock this knowledge. In order for research to be successful, many factors need to be taken into consideration including time and money. Often forgotten is the hidden cost of manual abstraction of patient charts. It is both costly and inefficient to fit the needs of individual research projects least not the institution as a whole. In this webinar we will discuss use cases where Artificial Intelligence - Natural Language Processing (AI-NLP) has made an impact on the success of research projects- from adding vital information to clinical registries, speedy identification of research cohorts to feeding unstructured data into Machine Learning.

You will learn how AI-NLP impacted:

  • Phenotype extraction (i.e. suspected genetic disorders)
  • Adding unstructured elements and associated attributes to clinical registries (i.e. cancer)
  • Identifying patients for clinical and observational studies
  • Mine scientific literature for insights into genetic mutation and disease association
  • Identify Social Determinants of Health (SDoH)
  • Adding unstructured data to Machine Learning (ML) models 


Liz Marshall, MD, Director Clinical Analytics, Linguamatics

Dr. Marshall is committed to utilizing technology to promote better health. She is especially interested in utilizing Artificial Intelligence solutions such as Natural Language Processing (NLP) to promote enhanced patient care and medical research. Early in her career, she served in the United States Air Force, where her role in computer operations and logistics was in support of Operation Enduring Freedom, the military’s response to the 9-11 Attacks. After her military career, she became a research physician in the area of mental health and dedicated her time to the development of informatic solutions to improve clinical treatment of Military Veterans.  Her work as a Clinical Research Health Scientist at the Veterans Administration in Charleston, SC resulted in substantial gains in the treatment of suicidality and PTSD. She was awarded the 2013 Research Training Institute Scholar Award from the Injury Control Research Center for Suicide Prevention (ICRC-S). Marshall also developed a highly effective e-learning training program for helping clinicians identify and treat suicidal patients, that was requested for federal-wide adoption by the Department of Defense. Marshall has reviewed and abstracted relevant physical and mental information from EHR’s over 1,000 patients and 300 clinicians. Prior to joining Linguamatics, Marshall completed her fellowship training in informatics at the Medical University of South Carolina. There she earned Epic Research Clinical Certification and worked building informatic solutions for healthcare utilizing Linguamatics, Epic, and Telehealth.