When:
Time: 9:00am PDT, 12:00pm EDT, 5:00pm BST, 6:00pm CEST
Duration: 60 minutes
Amidst the explosion of interest generated from the launch of publicly available large language models, there has been a widespread realization of the potential value of information and insights previously trapped within unstructured medical records. Many use cases and applications are being proposed and tested, from population health to precision medicine, document creation and summarization and disease progression prediction. In this webinar – Dr Yacoubian will present real world examples of Natural Language Processing being deployed and used in healthcare and discuss generative AI in the context of an evolving field of AI that is already being used extensively within healthcare settings.
This webinar will cover use cases such as real time screening for Social Determinants of Health from patients’ medical records, the use of NLP to drive research in precision medicine and oncology, and human in the loop workflows that enable NLP to impact both clinical care, and administrative use cases.
Speakers
Calum Yacoubian
Director NLP Healthcare StrategyCalum Yacoubian
Dr. Calum Yacoubian is Director of Healthcare Product & Strategy at Linguamatics, IQVIA. He is a medical doctor who trained and practiced in the UK before moving into medical technology. He has worked with Natural Language Processing in clinical data for over 5 years and is passionate about the potential for data to drive improved patient outcomes.
Celeste Adams
NLP Application ScientistCeleste Adams
Celeste Adams, PharmD serves Linguamatics, IQVIA as an Application Scientist. She is a pharmacist that has practiced in retail, informatics, and medical terminology. Celeste has over 20 years of experience and has worked with Natural Language Processing (NLP) in clinical data for the past 8 years.
Celeste’s work has focused on using terminology and automated strategies such as NLP to facilitate various use cases in clinical practice from population health to disease identification. She has spent the large part of her career in teaching and training users to understand how to ask questions of any data (EHR, literature, social media). She has worked closely with all organizations such as academic medical centers, healthcare plans, and specialty vendors
