PRL07 Phenotyping Hidradenitis Suppurativa (HS): Findings of a Collaborative Artificial Intelligence (AI) Initiative
DESCRIPTION
This session will present how innovative AI modeling can identify a distinct hidradenitis suppurativa (HS) phenotype comprising data elements from patients' health histories. This phenotype can distinguish HS patients who may otherwise remain undiagnosed from the broader population, providing clinical insight and the potential for reduced time to diagnosis and treatment. Such innovations can be applied to help recognize other diseases, allowing earlier access to treatment, and ultimately decrease patient suffering.
LEARNING OBJECTIVES
Demonstrate how a heterogeneous open claims data source augmented with EHR data, can be used to identify patients with hidradenitis suppurativa (HS).
Examine how AI can be used to isolate disease profiles to identify patients for early intervention and targeted treatment.
Compare the predictors of HS diagnosis identified by AI with the existing literature and our current understanding of the disease
SCHEDULE
1:00 PM
Our AI model for finding undiagnosed HS: Overview
Steven Daniel Daveluy, MD, FAAD
1:10 PM
Discussion
Martina J. Porter, MD, FAAD
1:20 PM
Discussion
Amit Garg, MD, FAAD
1:30 PM
Questions and Answers
DIRECTOR
Steven Daniel Daveluy, MD, FAAD
Wayne State University
DISCLOSURES
Steven Daniel Daveluy, MD, FAAD
AbbVie – Advisory Board(Honoraria), Consultant (1099 relationship)(Honoraria), Speaker(Honoraria); Incyte – Advisory Board(Honoraria); Insmed – Investigator(Grants/Research Funding); MoonLake Immunotherapeutics – Investigator(Grants/Research Funding); Novartis – Speaker(Honoraria); Pfizer Inc. – Investigator(Grants/Research Funding); Regeneron – Investigator(Grants/Research Funding); Sanofi – Investigator(Grants/Research Funding); UCB – Consultant(Fees), Investigator(Grants/Research Funding), Speaker(Honoraria);