Time: 10:00am PDT, 1:00pm EDT, 6:00pm BST, 7:00pm CEST
Duration: 60 minutes
Healthcare benefits from Artificial Intelligence (AI) and Natural Language Processing (NLP) to drive efficiency and improve patient outcomes.
Artificial intelligence (AI) holds a promise of advancing our ability to improve patient care. Trained on routinely collected healthcare data, AI algorithms can identify patients at risk for a variety of medical events such as lingering misdiagnosis, disease progression, an upcoming severe adverse event, or non-adherence. Healthcare data can originate from structured fields (e.g., diagnoses captured via ICD-10) but 80% of data in the healthcare setting is unstructured, locked in sources such as radiology reports, discharge summaries and pathology notes.
This webinar will provide an overview of proven AI applications for medical event prediction, the types of data feeding into such applications and Natural Language Processing (NLP) techniques for transforming complex unstructured text into analysis ready data. We will showcase real-world applications of such AI algorithms, including a research engagement with Juvenile Diabetes Research Foundation to identify misdiagnosed type 1 diabetes patients in EMR data.
Topics covered during the webinar include:
- What AI and NLP are
- How NLP can enrich and normalize healthcare data for use in downstream analytics.
- How AI can transform data into actionable insights to enhance clinical care and research to improve patient outcomes
- About a real-world use case leveraging these analytical techniques
This webinar will be presented by Calum Yacoubian, Associate Director NLP Healthcare Strategy at Linguamatics, Nadea Leavitt, Senior Director, AI for Healthcare & MedTech at IQVIA and Sanjoy Dutta, Vice President, Research, Juvenile Diabetes Research Foundation.