Linguamatics Virtual NLP Summit Kick Off Event

May 19, 2020
Venue: , United Kingdom

When: Tuesday 19th May 2020

Time: 10:30am EDT; 7:30am PDT; 3:30pm BST; 4:30pm CEST.

Duration: 2 hours 10 minutes

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Agenda

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

Speakers

Phil Hastings
Phil Hastings
Linguamatics
John Brimacombe
John Brimacombe
Linguamatics
Ashley George
Ashley George
Bay Digital Consulting
David Milward
David Milward
Linguamatics
Mathias Leddin
Mathias Leddin
Roche
Alyssa Hahn
University of Iowa
Jane Reed
Jane Reed
Linguamatics

Presentation Abstracts

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.