May 2, 2024: 12:00 p.m. - 5:00 p.m. ET
May 3, 2024: 12:00 p.m. - 4:05 p.m. ET
Description
This workshop will highlight innovative approaches using database mining, machine learning (ML) and artificial intelligence (Al) for improved detection and classification of sleep and circadian disorders, potentially paving the way for advanced therapeutic interventions. The utilization of ML and Al as a paradigm for improving disease identification, diagnosis and classification will be examined, extending its implications beyond sleep disorders to encompass a broad spectrum of heterogeneous and multifactorial diseases. The workshop will include an introduction to NHLBl's BioData Catalyst, highlighting the features and capabilities of the platform and its applicability to disorders of sleep and circadian rhythms.
Key Objectives:
- To harness the rich, but under-utilized, multi-dimensional data collected from polysomnography (PSG) -including, oscillations of sleep, cardiac, and respiratory signals - to innovate diagnostic and patient management strategies.
- To discuss recent approaches and emerging concepts regarding the influence of sleep health on various health outcomes, along with the associated advantages and challenges.
- To integrate sleep-related physiological data with demographic, behavioral, genetic, genomic, and other biological, psychosocial, and lifestyle variables for a holistic analysis of the factors influencing sleep and its disorders.
Agenda
Videocast links
Thursday, May 2, 2024 at 12:00 PM - https://videocast.nih.gov/watch=54773
Friday, May 3, 2024 at 12:00 PM - https://videocast.nih.gov/watch=54776