Linguamatics Virtual NLP Summit Kick Off Event
Driving Innovation from bench to bedside with NLP
10:30 am Phil Hastings (Linguamatics) - Introduction
10:35 am John Brimacombe (Linguamatics) - Welcome Address
10:55 am Ashley George (Bay Digital Consulting) - Digital transformation in Life sciences — BUT what the heck are we transforming to?
11:15 am David Milward (Linguamatics) -Building an NLP Data Factory (High Quality Automated Data Processing using NLP and ML)
11:45 am Mathias Leddin (Roche) - Patient Insights from Social Media
12:05 pm Alyssa Hahn (University of Iowa) - The Use of Natural Language Processing to Improve Phenotype Extraction for Precision Medicine
12:25 pm Jane Reed (Linguamatics) - Addressing COVID-19
12:45 pm Phil Hastings (Linguamatics) - Wrap Up
Alyssa Hahn, Univeristy of Iowa
The Use of Natural Language Processing to Improve Phenotype Extraction for Precision Medicine
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. An on-going project at the University of Iowa 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.
This presentation will discuss how the University of Iowa is using NLP to transform unstructured source data into clinical and research decision support insights. It will review:
How NLP has reduced time-consuming and exhaustive manual chart reviews to extract phenotypic characteristics
The process of exporting critical clinical data from the EHR
Best training practices for the evaluation of NLP results to achieve high levels of accuracy.