Can AI solve some of Neonatology's greatest challenges?

Friday, May 3, 2024

3:45 PM – 5:15 PM ET

Location: Metro Toronto Convention Centre: 105

CE: Live CME: 1.5

Selected By: Neonatal
Co-sponsored By: PIDS

Chair(s)

Wissam Shalish, MD PhD

Neonatologist
McGill University Faculty of Medicine and Health Sciences
Montreal, Quebec, Canada
Zachary Vesoulis, MD, MSCI

Assistant Professor
Pediatrics
Washington University in St. Louis School of Medicine
St. Louis, Missouri, United States

Disclosure(s):

Wissam Shalish, MD PhD: I do not have any relevant financial / non-financial relationships with any proprietary interests.

Zachary A. Vesoulis, MD, MSCI: Edwards LifeSciences (Ongoing) (Products/Services: Research Support including clinical trials & the principal or named investigator); Medtronic (Ongoing) (Products/Services: Consultant, Research Support including clinical trials & the principal or named investigator)

Session

Description: Machine learning (ML) and artificial intelligence (AI) technologies have been used in medicine since the 1950s with numerous FDA approved models already being incorporated into clinical care for adult medicine. Neonatology, specifically, has a unique opportunity to leverage AI and ML research due to the complexity and volume of neonatal critical care data. In this exciting session we will explore both pioneering and emerging research that employs AI and ML to address some of Neonatology’s greatest challenges.

Enjoy a group of international experts spanning diverse career stages discussing specific examples of current tools and future research using AI and ML, focusing on:
1. Predictive analytics in Neonatal Sepsis
2. Forecasting extubation success rates
3. Data-driven insights into bronchopulmonary dysplasia and necrotizing enterocolitis
4. Emerging global tools in retinopathy of prematurity detection

We will commence with a succinct overview of the session objectives and each talk will follow the format of historical context, emerging technologies, and discussion on the limitations and benefits of using these models clinically. Geared towards a general pediatric and neonatology audience, the discussions will emphasize clinical outcomes and future prospects, without delving into technical details of the algorithms.

There will be 30 minutes at the end of this session for discussion and Q&A. Don't miss this opportunity to be at the forefront of Neonatology's technological transformation!

Learning Objectives:

To understand the historical context and ongoing advancements of AI and ML applications in neonatal care.
To review currently used and emerging AI and ML models
To critically evaluate the limitations, benefits, and future applications for using AI and ML approaches in research.

Presentations:

3:45 PM – 3:55 PM ET

Introduction to AI in Neonatology: Is it already here?
Speaker: Wissam Shalish, MD PhD – McGill University Faculty of Medicine and Health Sciences
3:55 PM – 4:05 PM ET

Predicting Neonatal Sepsis: Is one RCT enough evidence?
Speaker: Brynne Sullivan, MD, MSCR (she/her/hers) – University of Virginia School of Medicine
4:05 PM – 4:15 PM ET

Forecasting extubation success rates: will our predictions help or harm?
Speaker: Lindsey A. Knake, MD (she/her/hers) – University of Iowa Roy J. and Lucille A. Carver College of Medicine
4:15 PM – 4:25 PM ET

BioPulmoInformatics: Advancing Bronchopulmonary Dysplasia with Data
Speaker: Alvaro Moreira, MD, MSc – The University of Texas Health Science Center at San Antonio Joe R. and Teresa Lozano Long School of Medicine
4:25 PM – 4:35 PM ET

NEC: Can predictions lead to prevention?
Speaker: Thomas Hooven, MD (he/him/his) – University of Pittsburgh School of Medicine
4:35 PM – 4:45 PM ET

Emerging global tools in ROP Detection: Are we already behind?
Speaker: Ryan M. McAdams, MD (he/him/his) – University of Wisconsin School of Medicine and Public Health
4:45 PM – 5:15 PM ET

Q&A
Speaker: Zachary A. Vesoulis, MD, MSCI – Washington University in St. Louis School of Medicine