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

University of Iowa NLP-Based Phenome Extraction from the EHR

(October 24, 2019) |

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Webinar Description:

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 Natural Language Processing (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

Who Should Attend

Pharma and Biotech – VPs, Directors, or Heads of research teams:

• Working in target selection, drug discovery, precision medicine
• Have teams of researchers, scientists, working to understand the associations between specific gene, complex or rare disease (or actually any disease), and genetic relationships, gene variants, etc.
• Want to reduce the manual curation effort needed to gain insights scientific literature

Healthcare Providers, and Academic Medical Centers – Chief Research Information Officer, Clinicians, Principle Investigators for large scale genotype/phenotype projects

• Working in precision medicine
• Have a large scale genotype/phenotype project with 10,000s of subjects
• Want to reduce the manual curation effort needed to gain healthcare insights from unstructured patient narratives

Speakers:

Benjamin W. Darbro

Univ of Iowa

Alyssa Hahn

Univ of Iowa

Simon Beaulah

Linguamatics, an IQVIA company

(October 24, 2019) |